Stock Size Research Articles

Willingness and capacity of borrowers for loan repayment among farmers in Delta State Nigeria

Willingness of borrowers to repay loan and their capacity to repay borrowed fund has been an enigmatic challenge in the financing of agricultural enterprises in the tropics. As it stands, there is lack of empirical information on willingness of borrowers to repay loan and their capacity to repay credit. Investigating this challenge will improve agriculture in Delta state, Nigeria. This study derives its significance from its implications and usability among credit institutions. This study investigates willingness and capacity of borrowers for credit repayment among farmers in Delta State, Nigeria. A multistage sampling approach was used to select 216 farmers, Descriptive statistics, multiple regression, and binary logistic regression were employed in the analysis of collected data. The findings of the study show a mean amount of ₦460,972.22 was borrowed and ₦253,268.52 was repaid with a loan repayment performance of 54.94% and loan default rate of 45.1%. Further result indicates that 56.5% of farmers express willingness to repay loans, while 43.5% show unwillingness to repay borrowed fund. Further finding reveals that 40% of the farmers possess capacity to repay loan.. The study revealed that there is a significant difference in loan repayment capacity of poultry< fish, < arable crop farmers, with an F-value of 5.669 and (P≤ 0.05). Regression analysis identifies significant predictors of loan repayment capacity to include stock size, off-farm income, and farm income. Diversified income sources and effective farm management practices play crucial roles. Logistic regression indicates that longer repayment periods, larger stock sizes, and greater farming experience positively influence farmers’ willingness to repay loans (P≤0.05). It was recommended among others that financial institutions should offering flexible loan terms and sizes according to borrowers capacity. Encouraging farmers to diversify their income sources can improve loan repayment capacity of farmers.

Testing the feasibility of quantifying change in agricultural soil carbon stocks through empirical sampling

There is disagreement about the potential for regenerative management practices to sequester sufficient soil organic carbon (SOC) to help mitigate climate change. Measuring change in SOC stocks following practice adoption at the grain of farm fields, within the extent of regional agriculture, could help resolve this disagreement. Yet sampling demands to quantify change are considered infeasible primarily because within-field variation in stock sizes is thought to obscure accurate quantification of management effects on incremental SOC accrual. We evaluate this ‘infeasibility assumption’ using high-density (e.g., 0.1 ha sample–1), within-field, sampling data from 45 cropland fields inventoried for SOC. We explore how more typical within-field sampling densities, as well as field numbers and magnitude of simulated change in SOC stocks, impacts the ability to accurately quantify management effects on SOC change. We find that (1) stock change estimates for individual fields are inaccurate and variable, where marked losses and gains in SOC stocks are frequently estimated even when no change has occurred. Higher sampling densities (e.g., 1.2 versus 4.0 ha sample–1) narrow the range of estimated stock changes but inaccuracies remain large. (2) The accuracy of stock change estimates at the project level (i.e., multiple fields) were similarly sensitive to sampling density. In contrast to individual fields, however, higher sampling densities, as well as a greater number of fields (e.g., 30), generated robust and accurate, mean project-level estimates of carbon accrual, with ∼ 80 % of the estimates falling within 20 % of the simulated stock change. Yet such monitoring designs do not account for dynamic baselines, which necessitates measurement of stock changes in control, non-regenerative fields. We find (3) that higher sampling densities (e.g., 1.2 versus 4.0 ha sample–1), field numbers (e.g., 30 versus 10 pairs of fields), and magnitudes of simulated SOC stock change (+3 and +5 versus +1 Mg C ha−1 10 y–1) are then collectively required to make accurate estimates of management effects on stock change at the project level. The simulated effect sizes that could be consistently detected under these conditions included rates of SOC accrual considered achievable and meaningful for climate mitigation (e.g., 3 Mg C ha−1 10 y–1), with field numbers and sampling densities that are reasonable given current sampling methods. Our findings reveal the potential to use empirical approaches to accurately quantify, at project scales, SOC stock responses to practice change. We provide recommendations for data that government, farmer and corporate entities should measure and share to build confidence in the effects of regenerative practices, freeing the SOC debate from overreliance on theory and data collected at scales mismatched with agricultural management.

ANALYSIS OF EFFECT OF SOCIO-ECONOMIC CHARACTERISTICS ON THE PERCEPTION OF FARMERS ON GIANT LAND SNAIL (Achatina achatina) PRODUCTION IN NORTH CENTRAL STATES, NIGERIA.

The study analysed Sixty-four snail farmers were sampled through multiple-stage sampling technique. Descriptive and inferential statistics were used to achieve the specific objectives of the study. The study found that snail farming was carried out by young active farmers whose average age was 44 years, with an average of 7 years experience in snail farming, small-scale in nature because their average stock size was 787 snails. The average household size and annual farm income was 6 persons and N350,000.50 respectively. The farmers’ perception was high (83%) for snail farming and this was linked to the several benefits like increased income, enhancement of family welfare, a source of animal protein, source of employment, means of turning kitchen waste and ways of engaging family labour, derived from snail production. Snail production was asserted to be low (55%) due to constraints like slow rate of growth, theft, pest and disease (just to mention but a few), the farming of snail was noted to be economically viable. Socio-economic characteristics such as farmers gender, age, education, marital status, household size and farm income were identified to be significant variables to level of snail production. By recommendation, there is need for research to focus on breeding snails that are early maturing and fast growing to help overcome the problem of slow growth and used by the farmers for production purpose.

Determinants and framework for implementing sustainable climate-smart aquaculture insurance system for fish farmers: Evidence from Ghana

The just-ended Sharm El-Sheikh Climate Change Conference in November 2022 brought to light the need to mitigate climate change adaptation related to risk and challenges through Climate financing, has made it very paramount the need to protect fish farmers' investments from climate change-related risk through the development of climate-smart insurance products and covers to help mitigate climate change effects on aquaculturists. As a result, this paper examines aquaculture farmers' preference for climate-smart aquaculture insurance products, challenges of climate-smart aquaculture insurance, and their preferred insurance cover. Survey data was collected from 140 fish farmers and analysed via Multinomial logistic regression, Bivariate Probit regression and Kendall's coefficient of concordance. Climate-Induced Aquaculture Stock Mortality Insurance (CIASMI) was the most-preferred climate-smart insurance product. Insurance Cover for Diseases (ICD) was the least preferred. The results further indicated that membership in a farmer organisation, farm income, credit access, climate-related peril and anthropogenic-related peril had a positive influence, whereas years of education had a negative influence on climate-smart aquaculture insurance participation.Moreover, production system had a negative relationship with mode of participation while number of employees, farm income and climate-related peril influenced mode of participation positively. The results also revealed that age, sex, stock size, awareness, income, climate and environmental-related peril, and anthropogenic-related peril significantly influenced the choice for climate-smart aquaculture insurance products, specifically climate risk related to stock mortality insurance and climate-related to consequential loss insurance. Finally, delay in claim settlement was the most pressing constraint. In contrast, lack of experts in disease diagnosis was the least ranked constraint of climate-smart aquaculture insurance. Therefore, this study provides insights for the Fisheries Commission, Ghana Agricultural Insurance Pool (GAIP), World Cover and other agricultural insurance companies globally to draft climate-smart insurance products for aquaculturists.

Determinants of Poultry Egg Farmers’ Participation in Livestock Insurance in Rivers State, Nigeria

Poultry farming is exposed to several hazards caused by epidemic diseases, climate change and marketing among others which lead to losses of revenue. Yet, majority of poultry farmers do not neither shared nor transferred their hazards rightly. In the light of this, this study examined the determinants of poultry egg farmers’ participation in livestock insurance in Rivers State, Nigeria. Primary data were obtained with the aid of questionnaire and interview schedules from 120 farmers drawn through multistage sampling procedure. Descriptive statistics and Probit regression model were used to analyze the data. Results shows the mean age of the poultry egg farmers to be 45.21 years, years spent in formal education mean of 14.87 years, mean household size of five (5), and stock size of 1721 birds were obtained. 60.8% were aware of livestock insurance and about 35% of the farmers insured their farms. Probit regression result shows that access to credit facilities, stock size and household size were statistically significant determining the poultry egg farmers’ participation in livestock insurance scheme. Poor agricultural extension service delivery and delay in indemnity payment among others were constraints encountered in participating livestock insurance. The study recommends that extension agents in collaboration with the insurance company providers should educate poultry farmers on livestock insurance role in risk management. Also, insurance companies should endeavor to keep terms of contractual arrangements not to delay in indemnity payment to the farmers.

Estimation of returning Atlantic salmon stock from rod exploitation rate for principal salmon rivers in England & Wales

Abstract For effective fishery management, estimated stock sizes, along with their uncertainties, should be accurate, precise, and unbiased. Atlantic salmon Salmo salar stock assessment in England and Wales (and elsewhere across the Atlantic) estimate returning salmon stocks by applying a measure of rod exploitation rate (RER), derived from less abundant fishery-independent stock estimates, to abundant fishery-dependent data. Currently, RER estimates are generated for individual principal salmon rivers based on available local data and assumptions. We propose a single, consistent, transparent, and statistically robust method to estimate salmon stocks that transfers strength of information from “data-rich” rivers, i.e. those with fisheries-independent data, to “data-poor” rivers without such data. We proposed, fitted, simplified, and then validated a Beta–Binomial model of RER, including covariates representing angler and fish behaviours, river flow, and random effects to control for nuisance effects. Our “best” model revealed covariate effects in line with our hypotheses and generalized to data not used to train it. We used this model to extrapolate stock estimates from 12 data-rich to 52 data-poor rivers, together with their uncertainties. The resulting river-specific salmon stock estimates were judged to be useful and can be used as key inputs to river-specific, national, and international salmon stock assessments.

Inventory Management with Demand Forecast for Eyeglass Lenses Using The Time Series Method at An Optical Store

In the healthcare sector, supply chain management is one of the most important elements since in the logistics of medical devices and pharmaceutical products, patient satisfaction is the main focus in efforts to improve service quality. One of the problems that often occurs in the optical supply chain is inventory control. The optical store is one of the microenterprises engaged in optometric health services. The enclosed supply chain is a three-echelon model, where the store is at the second level. The process of ordering lenses at the store from suppliers is not carried out based on predicted demand. The determination of the safety stock amount and the reorder point also still has a fairly low accuracy there. This is indicated by overstock and stock-out situations that still occur frequently in this company. Overstock causes the product to be damaged because it has been stored for too long and stock out causes lost sales. To solve the problem in this research, the prediction of future demand is overcome by using several time series methods, such as cyclical models, cyclical trend models, and ARIMA models. Forecasting result validation is implemented by calculating the calculation of errors using MAPE, MAD, and MSE then it was found that the forecasting model chosen to predict the demand for the lenses is a cyclical trend model. The result of the demand forecasting and safety stock size calculation with 3 service levels are used as input to determine the reorder point. After observing the condition of the company and the targets set by the company, the calculation results with a service level of 90% is the most possible to be implemented.

Homestead mechanized aquaculture in Bangladesh: New concept for enhancement for production and profitability

In Bangladesh, almost all of the homestead ponds are cultured extensively, where there are scopes to enhance productivity through aquaculture mechanization. Five household-sized ponds (60±0.02 decimal) were selected. No mechanization is done on Pond 1. Pond 2, Pond 3, Pond 4 and Pond 5 were equipped with surface aeration; Pond 3 was with Bottom aeration; Pond 4 and Pond 5 were equipped respectively with surface, bottom, combination of both and combination of both aerations along with additional automated feed sprayer. All ponds were stocked at a rate of 250 pcs. /decimal mono-sex Tilapia (Oreochromis niloticus) and the stocking size was 0.90±0.15 g. Water Temperature, pH, and dissolved oxygen (DO) were recorded two times daily, whereas Ammonia, Nitrate, Nitrite and Phosphate data were recorded fortnightly during the 124-day culture period. Highest average growth (266.08±12.80 g) and lowest Feed Conversion Ratio (1.10) were found in Pond 5, whereas the lowest average growth (153.70±48.07) and highest FCR (1.70) was found in Pond 1. Production was enhanced by 40%, 28%, 47% and 54% respectively in Pond 2, 3, 4 and 5; compared with the control Pond 1. Economic analysis showed that the profit increased by 13%, 25% and 41% in Pond 2, 4 and 5 respectively compared with control Pond 1. In Pond 3, profit decreased by 25% compared with control Pond 1. In all treatments, FCR is reduced, which is very important to maintain good water quality for homestead ponds. Economically These experiments need to be further developed for polyculture ponds, to find out the appropriate species combination, to serve partial harvest for household consumption and for more viable economic return.

New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method

Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the “Catch-MSY” method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge.

New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method

Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the “Catch-MSY” method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge.

Using the kanban system as an effective tool for organizing the transportation of dairy raw materials

The paper considers approaches to providing the enterprise with the required raw materials or semi-finished products. The general scheme of the milk raw material transportation cycle was analyzed. According to one approach, the supply system of raw materials can be represented by three constants, based on which several of their relations can be established, allowing us to describe the supply system much better. It is emphasized that the total duration of the cycle for each supplier is individual and depends on the demand indicator and the volume of the batch of the product or raw material. However, each product or raw material supplier's different cycle times do not allow them to be consolidated to build a stable delivery route. It is essential to achieve the required delivery frequency with maximum vehicle loading. The need to use the " heijunka board" to organize the efficient operation of routes for the transportation of dairy raw materials by the enterprise's employees was analyzed. Such a tool allows one to visualize dairy raw materials' transportation routes and ensure explicit control. For this, a heijunka board and supplier kanban cards are used, which form a graphic representation of transport routes in the corresponding time interval. Policy directions for determining the frequency of transportation of raw materials or semi-finished products are highlighted. It is proved that the optimal order policy must satisfy the zero-order property, and the time between orders can be calculated based on the amount of stock in the warehouse and the speed of their use, which will correspond to the demand indicator d and will reach zero after f orders. The kanban system allows optimal results in combination with the heizunk method, which balances the delivery time of raw materials or products as much as possible. Several models for the analysis of the heizunk system are considered. The common feature of these methods is the search for the optimal size of the buffer stock to ensure the maximum efficiency of production facilities while minimizing losses. The total number of kanbans for the system is decisive because this indicator determines the effectiveness of their adaptation to changes in production conditions. Keywords: kanban, system, heizunk method, loss minimization, order.

A global synthesis and conceptualization of the magnitude and duration of soil carbon losses in response to forest disturbances.

Forest disturbances are increasing around the globe due to changes in climate and management, deteriorating forests' carbon sink strength. Estimates of global forest carbon budgets account for losses of plant biomass but often neglect the effects of disturbances on soil organic carbon (SOC). Here, we aimed to quantify and conceptualize SOC losses in response to different disturbance agents on a global scale. Global. 1983-2022. Forest soils. We conducted a comprehensive global analysis of the effects of harvesting, wildfires, windstorms and insect infestations on forest SOC stocks in the surface organic layer and top mineral soil, synthesizing 927 paired observations from 151 existing field studies worldwide. We further used global mapping to assess potential SOC losses upon disturbance. We found that both natural and anthropogenic forest disturbances can cause large SOC losses up to 60 Mg ha-1. On average, the largest SOC losses were found after wildfires, followed by disturbances from windstorms, harvests and insects. However, initial carbon stock size, rather than disturbance agent, had the strongest influence on the magnitude of SOC losses. SOC losses were greatest in cold-climate forests (boreal and mountainous regions) with large accumulations of organic matter on or near the soil surface. Negative effects are present for at least four decades post-disturbance. In contrast, forests with small initial SOC stocks experienced quantitatively lower carbon losses, and their stocks returned to pre-disturbance levels more quickly. Our results indicate that the more carbon is stored in the forest's organic layers and top mineral soils, the more carbon will be lost after disturbance. Robust estimates of forest carbon budgets must therefore consider disturbance-induced SOC losses, which strongly depend on site-specific stocks. Particularly in cold-climate forests, these disturbance-related losses may challenge forest management efforts to sequester CO2.

Profit Analysis of Small-Scale Poultry Layers in Iwo Agricultural Development Programme (ADP) Zone of Osun State

This study focused on the profit analysis of small-scale poultry layers in Iwo ADP Zone of Osun State. Data were collected from the poultry farmers using a well-structured questionnaire and multi-stage sampling procedure. A total sample size of one hundred and five (105) poultry farmers was selected. Data were analyzed using descriptive statistics budgetary analysis and inferential statistical tools (OLS). Results of the study revealed that majority (80%) of the farmers were below 50 years and the farmers’ mean age was 49.5±7.7 years. The majority (95%) of the farmers had primary education and above. The mean year of experience was 11.0±3.4 years. The mean birds reared and profit was 405 birds and N84, 849.54 respectively. Return on investment during the period was N1.04 establishing positive returns. Household size, years of poultry farming experience and stock size were the factors significantly influencing the profit positively. Therefore, it is suggested that poultry farmers in the study area should try to increase their pen size, explore the use of family labour and endeavour to learn new methods of poultry management from farmers with more years of poultry-keeping experience to increase their level of profit.

The initial assessment of an important pelagic fish, Mackerel Scad, in the South China Sea using data‐poor length‐based methods

AbstractObjectiveScadsDecapterusspp. occur widely throughout tropical, subtropical, and temperate oceans and are both economically and ecologically important species. They are among the main commercial fish species caught by the light falling‐net fishery in the South China Sea, which is dominated by Mackerel ScadDecapterus macarellusand Shortfin ScadD. macrosoma. Stock assessment is an approach used to guide effective management and maintain fishery sustainability.MethodsTwo data‐poor methods, namely length‐based Bayesian biomass estimation and length‐based spawning potential ratio, were applied to assess the status of Mackerel Scad, the most dominantDecapterusspecies in the South China Sea. Electronic length–frequency analysis was used to estimate von Bertalanffy growth parameters (asymptotic lengthLinfand growth coefficientK) to serve as priors.ResultThe results show the estimatedLinfandKof Mackerel Scad in the South China Sea as 36.0 cm and 0.37/year, respectively. Estimated natural mortality was 0.74/year, and mean fork length at 50% sexual maturity was 24.29 cm. Length‐based Bayesian biomass estimation analysis showed that the estimated relative stock size had decreased from 1.3 in 2012–2014 to 0.7 in 2019–2021, indicating an overfished status. Length‐based spawning potential ratio analysis showed that the estimated spawning potential ratio for this fishery decreased from 13% to 12%, which is significantly below the limit reference point of 20%.ConclusionOur results obtained through length‐based methods indicate the lower SPR of Mackerel Scad stock was due to catching an excess of juveniles. Therefore, we highlight the need to increase the minimum mesh size in the fishing nets and strengthen international cooperation for conserving this shared stock in the South China Sea.

Stochastic modelling and synthesis of dynamic fish recruitment productivity in the Celtic Seas ecoregion

Abstract The Celtic Seas ecoregion (CSE) is undergoing climatic and ecosystem changes, which can induce changes in fish productivity. Globally, the productivity of many stocks has shown evidence of change over decadal timescales. Varying factors might drive these dynamics in the CSE, but for many stocks, these mechanisms have not been fully understood to be included in management advice. We study dynamic productivity for 28 stocks in the Celtic Seas by tracking integrated stochastic signals in the relationship between stock size and recruitment using state-space modelling applying Peterman’s Productivity Method. Our research objectives were to (i) fit Ricker stock–recruitment models with time-varying parameters to all age- or length-based assessed stocks in the CSE, (ii) evaluate which parameters vary in time, (iii) examine temporal characteristics of historical recruitment productivity, and (iv) evaluate productivity correlation across stocks. For 22 out of 28 stocks, at least one of the three time-varying parameter models had a better fit than the time-invariant model. In the CSE, fish productivity has diverse temporal patterns, with some stocks displaying relevant long-term decreasing productivity trends. Getting insight into temporal changes in recruitment productivity is very valuable and has important implications for sustainable fisheries.

Culture suitability of stinging catfish Heteropneustes fossilis in homestead tank: Selection of suitable stocking size

The present experiment was conducted for a period of 150 days to assess the effects of different stocking size on growth and production of stinging catfish (Heteropneustes fossilis) in three homestead cemented tanks (12×10×4 ft). Three different size groups of fish viz., 3.79±0.11, 3.09±0.13 and 2.53±0.18 cm was stocked at treatment T1, T2 and T3, respectively at a stocking density of 5000 individuals/tank each with three replications. Fish were feed twice daily with floating feed containing 35-40% protein at the rate of 15-10% for 1st 60 days, 8-6% for 2nd 60 days and 5-2.50% for rest of the culture period. The water quality parameters were within the suitable ranges for the fish culture. Mean weight gain (g) of stinging catfish was 49.03 ± 1.04, 36.72 ± 1.59 and 28.09 ± 0.41g, specific growth rate was 1.76 ± 0.02, 1.70 ± 0.04 and 1.66 ± 0.05 %/day in T1, T2 and T3, respectively. Food conversion ratio was 3.45 ± 0.82, 3.31 ± 0.10 and 3.30 ± 0.06 and survival rate were 90.67 ± 1.51, 88.20 ± 2.62 and 87.56 ± 1.26% in T1, T2 and T3, respectively. Higher stocking size also resulted in a significantly higher economic output in the form of benefit cost ratio (BCR) at T1 (2.13 ± 0.05) and the lowest at T3 (1.21 ± 0.03). The findings of the present study revealed that the highest weight gain and BCR was found in T1 which dictates that larger stocking size has a significant impact on better production.

The Northeast Atlantic and Mediterranean bluefin tuna fishery: Back from the brink

At the turn of the century, the Northeast Atlantic and Mediterranean bluefin tuna stock (BFT-E) appeared to be heading towards collapse. In 2006, a recovery plan was introduced with the purpose of restoring the stock. Stock size is now increasing. In fact, the stock is now believed to be sustainably harvested. The fishery is managed by ICCAT, a Regional Fisheries Management Organisation (RFMO). Several authors question the effectiveness of RFMOs. This paper analyses how cooperation has been achieved as well as the stability of the current cooperative management regime. A main conclusion of the analysis is that RFMO management of BFT-E is very successful. This brings hope for the management of high seas fisheries worldwide.

Spatial separation of larval sprat (Sprattus sprattus) and sardine (Sardina pilchardus) related to hydrographical characteristics in the North Sea

AbstractClupeid fish species are widely distributed and of highly variable stock sizes. In the North Sea, the common clupeid species are herring (Clupea harengus) and sprat (Sprattus sprattus), but during recent decades, the generally more southerly distributed sardine (Sardina pilchardus) have been more frequently observed. Comparative studies of early life stages of small pelagic clupeids are scarce, and their abilities to co‐exist and relations to environmental characteristics are vastly understudied. We here investigated and compared distributional patterns of co‐occurring larval sprat and sardine in the North Sea, hypothesizing that they are separated into spatial niches linked to specific hydrographical characteristics. Sampling was carried out by a large ring‐net during standard fish surveys (IBTS Q3) in August 2018, 2019, and 2020. Sprat larvae were found widespread across the area of investigation, with the highest concentration in the central North Sea off the eastern and northern flanks of Dogger Bank, where abundances could reach 20 larvae/m2. Sardine larvae, on the other hand, showed their highest abundances in the Southern and German Bights. Distributions of the two species appeared complementary, and statistical correlations were indicative of separate hydrographical niches, where sardine larvae resided in relatively warmer and fresher water. The relative abundances of sardine versus sprat varied between years. Sardine larvae were especially abundant in 2020, twice as abundant as sprat, and observations indicate increasing importance of sardines in the North Sea.

Economic Relations between Hungary and Czechia

Trends of the economic relations between Czechia and Hungary – from Hungarian point of view – are reviewed, based mainly on the data of statistics office (KSH) and on the National Bank of Hungary (MNB). Developments are examined in EUR throughout the study, thus evaluation is exempt from HUF exchange rate changes. The first part presents, based on KSH data, the external trade turnover changes between Hungary and Czechia in 1994–2022. Czechia is an important trade partner of Hungary. Timely changes in product structure are emphasized, the most recent state is presented, based on SITC and BEC nomenclature. Car industry turnover size and structure is presented. The role of Czechia in the external trade of services is significantly smaller than in that of goods, but trade increases faster in this field. The second part compares, based on MNB data, the size and divisional structure of the outstanding capital stock, showing that Czech enterprises in Hungary are more productive than the average foreign subsidiary.

Testing the feasibility of quantifying change in agricultural soil carbon stocks through empirical sampling.

Abstract There is disagreement about the potential for regenerative management practices to sequester sufficient soil organic carbon (SOC) to help mitigate climate change. Measuring change in SOC stocks following practice adoption at the grain of farm fields, within the extent of regional agriculture, could help resolve this disagreement. Yet sampling demands to quantify change are considered infeasible primarily because within-field variation in stock sizes is thought to obscure accurate quantification of management effects on incremental SOC accrual. We evaluate this 'infeasibility assumption' using high-density (e.g., 0.1 ha sample -1 ), within-field, sampling data from 45 cropland fields inventoried for SOC. We explore how more typical within-field sampling densities, as well as field numbers and magnitude of simulated change in SOC stocks, impacts the ability to accurately quantify management effects on SOC change. We find that (1) stock change estimates for individual fields are inaccurate and variable, where marked losses and gains in SOC stocks are frequently estimated even when no change has occurred. Higher sampling densities (e.g., 1.2 versus 4.0 ha sample -1 ) narrow the range of estimated stock changes but inaccuracies remain large. (2) The accuracy of stock change estimates at the project level (i.e., multiple fields) were similarly sensitive to sampling density. In contrast to individual fields, however, higher sampling densities, as well as a greater number of fields (e.g., 30), generated robust and accurate, mean project-level estimates of carbon accrual, with ~80% of the estimates falling within 20% of the simulated stock change. Yet such monitoring designs do not account for dynamic baselines, which necessitates measurement of stock changes in control, non-regenerative fields. We find (3) that higher sampling densities (e.g., 1.2 versus 4.0 ha sample -1 ), field numbers (e.g., 30 vs. 10 pairs of fields), and magnitudes of simulated SOC stock change (+3 and +5 versus +1 Mg C ha -1 10 y -1 ) are then collectively required to make accurate estimates of management effects on stock change at the project level. The simulated effect sizes that could be consistently detected under these conditions included rates of SOC accrual considered achievable and meaningful for climate mitigation (e.g., 3 Mg C ha -1 10 y -1 ), with field numbers and sampling densities that are reasonable given current sampling methods. Our findings reveal the potential to use empirical approaches to accurately quantify, at project scales, SOC stock responses to practice change. We provide recommendations for data that government, farmer and corporate entities should measure and share to build confidence in the effects of regenerative practices, freeing the SOC debate from overreliance on theory and data collected at scales mismatched with agricultural management.