Productivity Model Research Articles

Assessment of Labour Productivity and the Factors of Its Increase in European Union 27 and Ukrainian Economies

The article is devoted to identifying the impact of factors on the increasing labour productivity in the economies of the European Union-27 (EU-27) and Ukraine. The system of influencing factors that must be taken into account in the assessment of the labour productivity indicator was substantiated. The factors are based on the most significant indicators of innovative development (innovative activity; formation and the use of personnel; the state of use of fixed capital; the composition of the payroll budget; investment activity; and the use of working time). Based on the use of the method of linearization of the labour productivity model, the rating coefficients of the influence of factors for the economies of the EU-27 and Ukraine were determined. It has been proven that the following factors have a significant positive impact on labour productivity: an increase in the costs of scientific research and development; the growth of enterprises expenditures on research and development (R&D) in high-tech sectors; the increase in the share of scientific research personnel and researchers in the total number of the employed population; the growth of costs for the innovation of industrial enterprises; an introduction to the production of new technological processes and innovative types of products; the purchase of machinery, equipment, and software; an increase in the share of the employed population that has a basic higher education (bachelor’s degree); the growth in the share of the employed population that has a full higher education (master’s degree); the increase in the share of enterprises providing training; the increase in the capital–labour ratio; the technological equipment of labour; the machine equipment of labour; the renewal of fixed capital; and the increase in the level of intellectualization of fixed capital. The available reserves for increasing the labour productivity in EU-27 economies and Ukraine were clarified, and recommendations for managing the labour productivity in the conditions of innovative development have been provided. This study gains relevance when Ukraine has assumed the official status of an EU candidate country and the advantages and potential difficulties in the membership process should be evaluated. Labour productivity will be one of the key factors in the post-conflict recovery of the economy.

Photorespiration in eelgrass (Zostera marina L.): A photoprotection mechanism for survival in a CO2-limited world.

Photorespiration, commonly viewed as a loss in photosynthetic productivity of C3 plants, is expected to decline with increasing atmospheric CO2, even though photorespiration plays an important role in the oxidative stress responses. This study aimed to quantify the role of photorespiration and alternative photoprotection mechanisms in Zostera marina L. (eelgrass), a carbon-limited marine C3 plant, in response to ocean acidification. Plants were grown in controlled outdoor aquaria at different [CO2]aq ranging from ~55 (ambient) to ~2121 μM for 13 months and compared for differences in leaf photochemistry by simultaneous measurements of O2 flux and variable fluorescence. At ambient [CO2], photosynthesis was carbon limited and the excess photon absorption was diverted both to photorespiration and non-photochemical quenching (NPQ). The dynamic range of NPQ regulation in ambient grown plants, in response to instantaneous changes in [CO2]aq, suggested considerable tolerance for fluctuating environmental conditions. However, 60 to 80% of maximum photosynthetic capacity of ambient plants was diverted to photorespiration resulting in limited carbon fixation. The photosynthesis to respiration ratio (P E : R D) of ambient grown plants increased 6-fold when measured under high CO2 because photorespiration was virtually suppressed. Plants acclimated to high CO2 maintained 4-fold higher P E : R D than ambient grown plants as a result of a 60% reduction in photorespiration. The O2 production efficiency per unit chlorophyll was not affected by the CO2 environment in which the plants were grown. Yet, CO2 enrichment decreased the light level to initiate NPQ activity and downregulated the biomass specific pigment content by 50% and area specific pigment content by 30%. Thus, phenotypic acclimation to ocean carbonation in eelgrass, indicating the coupling between the regulation of photosynthetic structure and metabolic carbon demands, involved the downregulation of light harvesting by the photosynthetic apparatus, a reduction in the role of photorespiration and an increase in the role of NPQ in photoprotection. The quasi-mechanistic model developed in this study permits integration of photosynthetic and morphological acclimation to ocean carbonation into seagrass productivity models, by adjusting the limits of the photosynthetic parameters based on substrate availability and physiological capacity.

Drivers of site productivity for oak in Poland

The site index (SI) is the most commonly used and representative measure of the phytocentric approach; it evaluates the site productivity based on the stand height and age. In the case of mixed stands with complex structures, phytocentric methods are very limited, while in non-forest areas, they are not ap­plicable. In situations where the applicability of phytocentric methods is limited, the site productivity is de­termined by geocentric methods. Geocentric methods allow direct modelling of site productivity, expressed by SI predicted from various environmental variables. The aim of this study was to develop a geocentric model for oak. Site productivity expressed by SI was described by the environmental variables and stand characteristics. To develop the SI model, we used the data from 2490 NFI plots with dominant oak species (Quercus sessilis and Quercus robur). A generalized additive model was used in modelling site productivity. We documented a significant relationship between SI and the environmental variables, age of stands and stand density. Furthermore, the site productivity for oak is shaped by climate factors, soil type, geology, and altitude. The model developed based on the geocentric method, explained 55.1% of the variation of SI

Photosynthetic Carbon Uptake Correlates with Cell Protein Content during Lipid Accumulation in the Microalga Chlorella vulgaris NIES 227

Large-scale microalgae cultivation for biofuel production is currently limited by the possibility of maintaining high microalgae yield and high lipid content, concomitantly. In this study, the physiological changes of Chlorella vulgaris NIES 227 during lipid accumulation under nutrient limitation was monitored in parallel with the photosynthetic capacity of the microalgae to fix carbon from the proxy of oxygen productivity. In the exponential growth phase, as the biomass composition did not vary significantly (approx. 53.6 ± 7.8% protein, 6.64 ± 3.73% total lipids, and 26.0 ± 9.2% total carbohydrates of the total biomass dry-weight), the growth capacity of the microalgae was preserved (with net O2 productivity remaining above (4.44 ± 0.93) × 10−7 g O2·µmol PAR−1). Under nutrient limitation, protein content decreased (minimum of approx. 18.6 ± 6.0%), and lipid content increased (lipid content up to 56.0 ± 0.8%). The physiological change of the microalgae was associated with a loss of photosynthetic activity, down to a minimum (1.27 ± 0.26) × 10−7 g O2·µmol PAR−1. The decrease in photosynthetic O2 productivity was evidenced to correlate to the cell internal-protein content (R2 = 0.632, p = 2.04 × 10−6, N = 25). This approach could serve to develop productivity models, with the aim of optimizing industrial processes.

Prediction of truck productivity at mine sites using tree-based ensemble models combined with Gaussian mixture modelling

ABSTRACT In the past decade, machine learning (ML) algorithms have been widely applied to build prediction models for various mining applications. However, no research has been reported that forecasts truck productivity using ML algorithms. In this study, two tree-based ensemble learning algorithms, including random forest (RF) and gradient boosting regression (GBR), were proposed in combination with Gaussian mixture modelling (GMM) to train prediction models of truck productivity. GMM was adopted as a clustering technique to extract a latent variable from the training dataset. Multiple linear regression (MLR) and decision tree (DT) as single learning algorithms were used to construct prediction models to be compared with the tree-based ensemble models. The results showed that the tree-based ensemble models performed better than single models in predicting truck productivity with and without GMM clustering. Furthermore, GMM significantly increased the predictability of truck productivity prediction models by considering the latent variable. From the relative importance analysis, haul distance was the most influential factor among the observed input variables. Finally, the GMM-RF and GMM-GBR models with high accuracy were the proposed models for predicting truck productivity at mine sites.

Using the SCOPE model for potato growth, productivity and yield monitoring under different levels of nitrogen fertilization

Most applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and crop structure by exploiting the full solar reflective spectrum. In this study, we demonstrate how hyperspectral time series can be used with the Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model to estimate crop yield variability among fields, crop varieties and nitrogen treatments generically, i.e. without a calibration with in situ , data. Field experiments were conducted in two potato fields in the Netherlands between May and September 2019. The fields were planted with five varieties of potato, under three nitrogen fertilization treatments. By fitting the model to the full VNIR-SWIR spectrum of measured hyperspectral reflectance, we retrieved the model input parameters of Leaf Area Index (LAI), leaf chlorophyll content (Cab) and leaf water content (Cw) and simulated the photosynthesis throughout the season using data of local Automatic Weather Stations (AWS). Statistical analysis of measured and retrieved traits of LAI, Cab and canopy water content showed that two fields responded differently to the treatments, exhibiting fewer classes than were expected based on the experimental design. Potato yield, which was estimated as the sum of photosynthesis flux multiplied by the harvest index of 0.64, correlated with the measured tuber dry weight with R 2 0.36 and RMSE 2.5 t ha −1 . This study demonstrates that even in the absence of crop or variety specific information, hyperspectral reflectance and local weather data ingested into SCOPE can explain a substantial part of the observed variability in yield among fields. • Time series of hyperspectral canopy reflectance were recorded in two potato fields. • The variation in traits was created by nitrogen fertilization treatments. • SCOPE model retrieved plant traits contained information about treatments. • SCOPE-simulated accumulated photosynthesis correlated with the final dry yield. • SCOPE model is more generic than dimensionality reduction methods.

Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian.

The equal odds baseline model of creative scientific productivity proposes that the number of high-quality works depends linearly on the number of total works. In addition, the equal odds baseline implies that the percentage of high-quality works and total number of works are uncorrelated. The tilted funnel hypothesis proposes that the linear regression implied by the equal odds baseline is heteroscedastic with residual variance in the quality of work increasing as a function of quantity. The aim of the current research is to leverage Bayesian statistical modeling of the equal odds baseline. Previous work has examined the tilted funnel by means of frequentist quantile regression, but Bayesian quantile regression based on the asymmetric Laplace model allows for only one conditional quantile at a time. Hence, we propose additional Bayesian methods, including Poisson modeling to study conditional variance as a function of quantity. We use a classical small sample of eminent neurosurgeons, as well as the brms Bayesian R package, to accomplish this work. In addition, we provide open code and data to allow interested researchers to extend our work and utilize the proposed modeling alternatives.

Remote sensing-based vegetation indices for monitoring rice crop phenology and productivity in cikakak sub-district, sukabumi regency

Paddy is the main food crop consumed by most of the Indonesian daily. It is supported by the fact that rice consumption reached up to 1.55 tons in 2018, and Sukabumi Regency is among the five largest rice producer in Indonesia. The goal of this study is to determine the rice crop phenology and estimate rice productivity in one year of the planting season. The rice crop phenology was analyzed by comparing vegetation indices such as NDVI, ARVI, and MSAVI in different temporal situations. Vegetation indices derived from Sentinel-2 imageries via Google Earth Engine. A rice crop productivity model developed from the statistical relationship between in-situ-based productivity data and vegetation indices applied to estimate productivity per each paddy field at a sub-district level. Also, the estimation will be associated with elevation data. The results of this study are the pattern of the rice crop phenology and the number of harvesting time in one year-planting season. The rice productivity in the Cikakak sub-district estimates at the range between 6.50 to 8.87 tonnes per hectare. Estimation models utilizing NDVI and MSAVI are showing similar results, which averagely at 8.89 and 8.87 tonnes per hectare, respectively. Rice fields with high productivity are mostly located at 250 to 500 meters above sea level.

Productivity Model of Labour on Construction Projects in Indonesia

Productivity Model of Labour on Construction Projects in Indonesia

Performance of Diversified Legume Entailing Ultra High Intensity Rice based Cropping System Models for Higher Productivity, Profitability and Sustainability

Background: An intensive cropping system involving legume and vegetable crops not only highly productive and profitable but should also be stable over time and maintains soil health in present scenario. So, keeping this point in view the present investigation was carried out to evaluate the productivity, profitability and sustainability of legume entailing different ultra high intensity rice based cropping system models under irrigated sub-tropics. Methods: The field experiment was conducted at Research Farm, SKUAST-Jammu, Main Campus, Chatha for two consecutive years from kharif 2019 to summer season of 2021. The experiment consisting of five legume entailing rice based cropping system models of cropping intensity varying from 300-600% viz. T1: Rice (Basmati-370) - Wheat (HD-3086) - Cowpea (Lobia Super-60) having 300% cropping intensity, T2: Rice (Basmati-564) - Potato (Kufri Badshah) - Wheat (Raj-3765) - Mixed fodder (Maize+Cowpea+Charri in 2:2:1 ratio) having 400% cropping intensity, T3: Rice (SJR-129) - Knol khol (G-40) - Potato (Kufri Sindhuri) - Green gram (IPM 02-3) having 400% cropping intensity, T4: Rice (Pusa-1121) - Radish (CR-45) - Green onion (Nasik Red) - French bean (Anupama) - Okra (Seli special) having 500% cropping intensity in relay cropping from fourth crop onwards and T5: Rice (IET-1410) - Fenugreek (JF-07) - Knol khol (G-40) - Green onion (Nasik Red) - Dry onion (Selection-1) - Black gram (Pant U-19) having 600% cropping intensity in relay cropping from third crop onwards was laid out in a randomized block design with four replications. Result: The results obtained under two years research study revealed that treatment T4 recorded significantly highest basmati-370 rice equivalent system productivity followed by treatment T5. Further, treatment T4 also recorded highest system cost of cultivation, system gross returns and system net returns. System soil fertility status in terms of available NPK after completion of second crop cycle was significantly affected. Among different cropping systems, significantly higher available nitrogen and phosphorus were recorded in treatment T5 system which was at par with treatment T4.

A productivity prediction method for multi-fractured horizontal wells in tight oil reservoirs considering fracture closure

The closure fracture phenomenon increases the complexity of well testing and reduces the accuracy of productivity forecasts when tight oil reservoirs are exploited. However, most existing productivity models tend to ignore this. Therefore, a productivity prediction model for multi-fractured horizontal wells in tight oil reservoirs considering fracture closure has been developed by considering the stress sensitivity in the formation and combining the physical parameters of actual production. The model is solved by the Laplace transform, perturbation transform, Pedrosa transform, and Stehfest numerical inversion. Drawing productivity impact curves and discussing productivity influence factors based on the model results from this study show that the model is reasonable. In the actual production process, the hydraulic fracture parameter values are not as high as possible, and they have a reasonable range of values. The fracture closure pressure has a significant impact on the production of tight oil reservoirs. The higher the fracture closure pressure is, the greater the fracture conductivity decreases sharply, and the larger the proppant elastic modulus is, the stronger the fracture conductivity. The influence of fracture conductivity on the production in tight oil reservoirs has an obvious point, and when the value is less than the point, the production effect is good. Improved production can be achieved by balancing the relationship between fracture parameters. The findings of this study can help to better understand the influence of fracture parameters on productivity and contribute to increasing well production and improved development of tight oil reservoirs.

Stand Structural Characteristics Derived from Combined TLS and Landsat Data Support Predictions of Mushroom Yields in Mediterranean Forest

Forest fungi provide recreational and economic services, as well as ecosystem biodiversity. Wild mushroom yields are difficult to estimate; climatic conditions are known to trigger temporally localised yields, and forest structure also affects productivity. In this work, we analyse the capacity of remotely sensed variables to estimate wild mushroom biomass production in Mediterranean Pinus pinaster forests in Soria (Spain) using generalised additive mixed models (GAMMs). In addition to climate variables, multitemporal NDVI derived from Landsat data, as well as structural variables measured with mobile Terrestrial Laser Scanner (TLS), are considered. Models are built for all mushroom species as a single pool and for Lactarius deliciosus individually. Our results show that, in addition to autumn precipitation, the interaction of multitemporal NDVI and vegetation biomass are most explanatory of mushroom productivity in the models. When analysing the productivity models of Lactarius deliciosus, in addition to the interaction between canopy cover and autumn minimum temperature, basal area (BA) becomes relevant, indicating an optimal BA range for the development of this species. These findings contribute to the improvement of knowledge about wild mushroom productivity, helping to meet Goal 15 of the 2030 UN Agenda.

Study on the environmental efficiency of agricultural water resources about typical cropping patterns around the Dongting Lake area

Abstract This paper aims to evaluate the environmental efficiency of agricultural water resources utilization in different cropping patterns in the Dongting Lake area. To achieve that, the following materials are used: (1) study area: 16 counties (cities and districts) of Yueyang, Changde, and Yiyang around the Dongting Lake area; (2) data: relevant indicators of economic and environmental benefits of agricultural water resources utilization from 2011 to 2020; and (3) model: the Luenberger productivity model based on the directional distance function. With all the materials above, this paper calculates the environmental efficiency of typical cropping patterns in the Dongting Lake ecological zone and explores the spatial and temporal evolution patterns of typical cropping patterns in the lake area. The results show that (1) the environmental efficiency (LEI) of four typical cropping patterns in 16 counties (cities and districts) around Dongting Lake shows an overall increasing trend from 2011 to 2020, especially the environmental efficiency of four cropping patterns has increased significantly since 2014. (2) Among the four typical cropping patterns, the environmental efficiency of one-season rice + lobster is higher, and the environmental efficiency value of two-season rice + winter leisure is lower but most significantly improved. (3) The environmental efficiency of agricultural water resources in the hilly areas around the lake is higher than that in the Dongting Plain. Finally, some countermeasures and suggestions were put forward, such as implementing the reduction and efficiency of pesticide and chemical fertilizer in the planting industry in the lake area, optimizing the rice + planting mode, strengthening the construction of water conservation projects in the four river basins, and promoting high-standard farmland water-saving irrigation.

KONFEKSİYON ÜRETİMİNDE İŞGÜCÜ VERİMLİLİK ANALİZİNİN PANTOLON DİKİM HATTINDA UYGULANMASI

In order not to lose their market share in global markets where borders have disappeared, to gain competitive advantage, and to increase their profitability, businesses have increased their work on efficiency values to use their scarce resources effectively. Considering that global economies, of which importance is frequently mentioned today, are composed of national economies, and national economies are constituted by the economies of enterprises operating in that nation, it becomes evident how important they are. Improving the economies of businesses operating in countries is possible by minimizing unnecessary activities in production activities with various efficiency studies and reducing production-related costs. In this study, the workforce efficiency in a clothing company manufacturing trousers was analyzed. In this context, data was collected from the sewing line of a garment company operating on trouser production in Izmir, and the data obtained was evaluated with the labor productivity model with rates from Kurosawa's productivity models. As a result of this research, it has been determined that the losses expected to be eliminated entirely after getting used to the production of the relevant product are still visible and even more than they should be.

Unravelling net primary productivity dynamics under urbanization and climate change in the western Himalaya

Over the past few decades, climate change and urban expansion have strongly affected vegetation dynamics and overall carbon sink capacity of Himalayan ecosystem. However, the contribution of these two key factors on varying spatio-temporal scales in Himalayan landscapes still lacks in profound analyses. The present study takes Dharamsala and Pithoragarh urban landscapes as examples and uses the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) as the image fusion technique to generate highly resolved, both spatially (30 m) and temporally (monthly), NDVI images. These are used as inputs for Carnegie-Ames-Stanford Approach (CASA) model for Net Primary Productivity (NPP) estimation over the past two decades (2000–2020). During the study period, the NPP loss due to urbanization was 2065.43 kg C in Dharamsala and 401.07 kg C in Pithoragarh. Climate change, measured in terms of interseasonal changes in temperature, rainfall and solar radiation, had considerably contributed to the NPP variations of vegetated areas in both the study sites, however its contribution ratio was relatively lower than residual factors. There was a significant distribution gradient between how and where urban expansion and climate change influenced the NPP. Urban expansion impacts NPP more in plain areas corresponding to new urban land developments while climate change impacts NPP in high elevation mountainous regions dominated by Oak species. The observed declining trend of NPP under the current threat of urban expansion and climate change in the Himalaya highlights and invites the need of attributing importance to ecological issues. The findings of our study encompassing complex Himalayan landscapes could offer scientific perspectives for the management of ecological environment of highly fragile and vulnerable landscapes of the Himalaya.

Spatial Analysis of Cultivated Land Productivity, Site Condition and Cultivated Land Health at County Scale.

Cultivated land is a fundamental factor related to the social stability and sustainable development of the whole country. However, the safety of quantity and quality of cultivated land has decreased year by year, resulting in great challenges to the sustainable development of cultivated land. Cultivated land productivity, site conditions, and soil health jointly determine the sustainable development potential of cultivated land. Analyzing and calculating the coupling and cooperative relationship between these three subsystems can provide a theoretical and methodological reference for protecting and zoning cultivated land resources. Using Jiangyou City as a case study, this paper constructs a coupling coordination degree model of cultivated land productivity, site conditions, and soil health assessment systems in different geomorphic regions, and comprehensively analyzes the level of sustainable development of cultivated land in the study area. The results show that there are differences in the development potential of cultivated land resources in the mountainous regions in the north, the hilly regions in the center, and the plain regions in the south of Jiangyou City. The coupling coordination index of the three regions were calculated as 0.34, 0.51, and 0.63, respectively, for which the overall average coupling coordination index is 0.57; notably, it only reaches the “barely coordination” level. Based on our analysis results, the cultivated lands in Jiangyou City are classified into the following zones: core protection zone, dominant remediation zone, and key regulation zone. The cultivated land located in the core protection zone has a high coupling coordination index, which can be used as the preferred area for the delimitation of high standard basic farmland and permanent basic farmland. For the cultivated land located in the dominant remediation zone, the development of its subsystems is unbalanced. Comprehensive land improvement projects can be carried out in this zone to improve the overall quality. For the cultivated land located in the key regulation zone, it is recommended to implement projects such as returning farmland to forests to improve land use efficiency. In particular, the evaluation index system constructed in this paper is sufficiently representative, as it can support the classification, quality improvement, and sustainable use of cultivated land. Thus, other similar countries and regions can learn from the evaluation system constructed in this paper.

Productivity Improvement Strategy Analysis Palm Oil in Sumatra Province 2011-2021

This study uses a weighted index model and a productivity model where Aceh Province is the province with the highest weighted ranking value with a weighted value of 2.06, meaning that Aceh Province to obtain 1 ton of palm oil requires an average area of 2.06ha. Meanwhile, North Sumatra Province is the province with the lowest weighted index value when compared to other Sumatra Provinces, namely with a weighted value of 3.62, meaning that to obtain 1 ton of palm oil, an area of 3.62 Ha is needed. The highest productivity of palm oil production is in Aceh Province at 49.16% while the lowest palm oil production productivity is in North Sumatra Province at 27.98%. The strategy to increase the added value of palm oil production in Sumatra Province is through mapping of smallholder and company palm oil production areas, regulations for the sustainability of palm oil production, provision of subsidized fertilizer assistance for oil palm farmers, especially smallholder farmers and supervision and assistance to oil palm farmers in selecting seeds and processing land.

Productivity Prediction and Simulation Verification of Fishbone Multilateral Wells

As fishbone multilateral wells are increasingly used in the development of oil and gas fields, the need for the optimal design of multilateral well parameters has become increasingly urgent. Although the establishment of multilateral well productivity models has taken a step forward due to recently contributed research results, there are still few studies on model verification; that is, these models lack verification, and their reliability is uncertain, which increases the difficulty of their promotion and application in practice. Therefore, based on a more comprehensive horizontal well productivity prediction model, a fishbone multilateral well productivity prediction model was established in this work. Taking an oil field in the Middle East as an example, multilateral well productivity prediction and parameters sensitivity analysis were carried out, and the results were compared with the simulation results determined by using CMG digital simulation software. The established model was verified in terms of branch length, branch angle, and branch output contribution. The conclusions reached by these two methods were consistent, which verified that the established model was reliable.

Forest Carbon Flux Simulation Using Multi-Source Data and Incorporation of Remotely Sensed Model with Process-Based Model

Forest carbon flux is critical to climate change, and the accurate modeling of forest carbon flux is an extremely challenging task. The remote sensing model (the MODIS MOD_17 gross primary productivity (GPP) model (MOD_17)) has strong practicability and is widely used around the world. The ecological process (the Biome-BioGeochemical Cycles Multilayer Soil Module model (Biome-BGCMuSo)) model can describe most of the vegetation’s environmental and physiological processes on fine time scales. Nevertheless, complex parameters and calibrations pose challenges to the application and development of models. In this study, we optimized all the input parameters of the MOD_17 model for the calibration of the Biome-BGCMuSo model to obtain GPP with continuous spatiality. To determine the contribution of input parameters to the GPP of different forest types, an Extended Fourier Amplitude Sensitivity Test (EFAST) was performed on the Biome-BGCMuSo model firstly. Then, we selected the sample points of each forest type and its different ecological gradients (30 for each type), using the GPP simulation value of the optimized MOD_17 model corresponding to the time and space scale to calibrate the Biome-BGCMuSo model, to drive the calibrated Biome-BGCMuSo, and we simulated the different forest types’ net primary productivity (NPP). According to dendrochronological measurements, the NPP simulation results were verified on the whole regional scale. The results showed that the GPP values of different forest types were highly sensitive to C:Nleaf (C:N of leaf), SLA1 (canopy average specific leaf area in phenological phase 1), and FLNR (fraction of leaf N in Rubisco). The coefficient of determination (R2) between the simulated forest NPP and the measured NPP was 0.64, and the root-mean-square (RMSE) was 26.55 g/C/m2/year. Our study aims to reduce uncertainty in forest carbon fluxes simulated by the Biome-BGCMuSo model, providing feedback for understanding forest ecosystem carbon cycling, vegetation productivity, and climate change.

Timber Provision on Soft Soils in Forests Providing Protection Against Natural Hazards: A Productivity and Cost Analysis Using the Koller 507 in the Horizontal Yarding Direction in Switzerland

Forest soils can be sensitive to traffic for various reasons, such as a high water table and the absence of sturdy ground, both of which can lead to fragile ground conditions under wet weather conditions. Extracting timber from such stands is a challenge, and cable-based systems might be the best option. While damage to the remaining stand and to the soil during extraction is not always avoidable, the use of cable-based systems completely eliminates ground-based traffic in the case of fully suspended loads and at least reduces soil compaction, soil surface damage and erosion. From a technical viewpoint, cable-based systems can be applied in most forest types and at almost any time if they are equipped properly and with an appropriate configuration (e.g. with all-terrain cable yarders). However, only a few previous studies have been focused on the productivity and related costs that can be expected when cable-based systems are used in flat and environmentally sensitive areas. Therefore, we evaluated a forest operation using a Koller tower yarder with the aim to develop a productivity model that makes it possible to predict the productivity of comparable yarding operations beforehand and estimate related costs. In June 2021, we collected data from 473 cubic metres over bark (m3ob) during 104.25 h of commercial operation. We analysed the resulting 276 work cycles using ordinary least squares regression models. We categorised the work steps into felling (28.3%), yarding (68.0%) and piling (3.7%). The average yarding cycle time was 10.77 ± 5.40 min and resulted in an average yarding productivity of 9.95 m3ob PMH15−1. The variable payload, which was suboptimal in the analysed case, was the predictor with the greatest impact on productivity. Production costs were 86.65 CHF m3ob−1 at roadside, corresponding to 80.59 € m3ob−1.