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Contributing to agricultural mix:analysis of the living standard measurement study - Integrated survey on agriculture data set.

ABSTRACT: The Living Standard Measurement Study- Integrated Survey on Agriculture (LSMS-ISA) is a General Household Survey (GHS) and a cross-sectional survey consisting of 22,000 households which is carried out periodically across the globe. Currently, the GHS has three panels consisting of 5000 households of the GHS collecting additional data on agricultural activities, other household income activities, and household expenditure and consumption, among others. This is to improve data from the agricultural sector and the linkage to other facets of households' characteristics and outcomes. The LSMS data-set, questionnaire, and basic information document are freely available online at: http://microdata.worldbank.org/index.php/catalog/2734.

SUBMITTER: Osabohien R

PROVIDER: S-EPMC6082989 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Contributing to agricultural mix:analysis of the living standard measurement study - Integrated survey on agriculture data set.

Osabohien Romanus R

Data in brief 20180727

The Living Standard Measurement Study- Integrated Survey on Agriculture (LSMS-ISA) is a General Household Survey (GHS) and a cross-sectional survey consisting of 22,000 households which is carried out periodically across the globe. Currently, the GHS has three panels consisting of 5000 households of the GHS collecting additional data on agricultural activities, other household income activities, and household expenditure and consumption, among others. This is to improve data from the agricultura ...[more]

PMID: 30101165

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Project description:BackgroundLeaching of nutrients from agricultural areas is the main cause of water pollution and eutrophication of the Baltic Sea. A variety of remedial actions to reduce nitrogen and phosphorus losses from agricultural holdings and cultivated fields have been taken in the past. However, knowledge about the risk of nutrient leaching has not yet reached many farmers operating in the water catchment area of the Baltic Sea.MethodsThe nutrient balance method known as "At the farm gate" involves calculating separate balances for nitrogen (N), phosphorus (P) and potassium (K). After estimating all the components of the nutrient balance, the total balance for NPK is calculated and the data obtained is expressed as the ratio of total change (surplus) to the area of arable land on a farm. In addition, the nutrient usage efficiency on a farm is also calculated. An opinion poll was conducted in 2017 on 3.6% (n = 31) of the farms located in commune of Puck. The total area of the farms including arable and grass land ranged from 5 to 130 ha with an average of 45.82 ha. The arable land was on average 30.79 ha ranging from 4.45 to 130 ha while the grassland averaged 12.77 ha and ranged from 0 to 53 ha.ResultsThe average consumption of mineral fertilizer in the sample population of farms was 114.9 kg N, 9.3 kg P, and 22.9 kg K·ha-1of agricultural land (AL), respectively. N balance in the sample farms being ranged from -23.3 to 254.5 kg N·ha-1AL while nutrient use efficiency ranged from 0.40% to 231.3%. In comparison, P surplus in the sample farms was 5.0 kg P·ha-1AL with the P use efficiency of 0.4-266.5%.DiscussionMean N fertilizer consumption in the tested farms was higher than the average usage across Poland and in the Pomeranian Voivodeship. However, mean consumption of potassium fertilizers was lower than mentioned averages. Mean P fertilizer consumption was higher than in the Pomeranian Voivodeship, but lower compared to the entire country. Generally, on the basis of designated research indicators of farm pressures on water quality, concentrations of total nitrogen and total phosphorus were obtained. CalcGosPuck (an integrated agriculture calculator) will help to raise farmers' awareness about NPK flow on farm scale and to improve nutrient management.

Project description:BackgroundA recent review found that 45% of meta-analyses included statistical errors, of which, the most common was the calculation of effect sizes based on standard error (SE) rather than standard deviation (SD) [the SE/SD mix-up].ObjectivesThe first aim of this study was to assess the impact of the SE/SD mix-up on the results of one highly cited meta-analysis. Our second aim was to identify one potential source of the SE/SD mix-up, by assessing how often SE is reported as a measure of sample variability in randomised controlled trials in sports medicine.MethodsWe checked for potential SE/SD mix-ups in a 2015 meta-analysis of randomised controlled trials reporting the effects of recreational football interventions on aerobic fitness in adults. We corrected effect sizes affected by SE/SD mix-ups and re-analysed the data according to the original methodology. We compared pooled estimates of effect sizes from our re-analysis of corrected values with those of the original study. To assess how often SE was reported instead of SD as a measure of sample variance, we text mined results of randomised controlled trials from seven sports medicine journals and reported the proportion reporting of SE versus SD.ResultsWe identified potential SE/SD mix-ups in 9/16 effect sizes included in the meta-analysis describing the effects of football-based interventions versus non-exercise control. The published effect size was standardised mean difference (SMD) = 1.46 (95% confidence interval [CI] 0.91, 2.01). After correcting for SE/SD mix-ups, our re-analysis produced a smaller pooled estimate (SMD = 0.54 [95% CI 0.37, 0.71]). The original pooled estimate for trials comparing football versus running interventions was SMD = 0.68 (95% CI 0.06, 1.4). After correcting for SE/SD mix-ups and re-analysis, the effect was no longer statistically significant (SMD = 0.20 [95% CI - 0.10, 0.49)]). We found that 19.3% of randomised controlled trials reported SE rather than SD to describe sample variability. The relative frequency of the practice ranged from 0 to 25% across the seven journals sampled.ConclusionsWe found the SE/SD mix-up had inflated estimates for the effects of football on aerobic fitness. Meta-analysts should be vigilant to avoid miscalculating effect sizes. Authors, reviewers and editors should avoid and discourage (respectively) the practice of reporting SE as a measure of sample variability in sports medicine research.

Project description:Improved versions of inositol-1,4,5-trisphosphate (InsP3) sensors were created to follow intracellular InsP3 changes in single living cells and in cell populations. Similar to previous InsP3 sensors the new sensors are based on the ligand binding domain of the human type-I InsP3 receptor (InsP3R-LBD), but contain a mutation of either R265K or R269K to lower their InsP3 binding affinity. Tagging the InsP3R-LBD with N-terminal Cerulean and C-terminal Venus allowed measurement of InsP3 in single-cell FRET experiments. Replacing Cerulean with a Luciferase enzyme allowed experiments in multi-cell format by measuring the change in the BRET signal upon stimulation. These sensors faithfully followed the agonist-induced increase in InsP3 concentration in HEK 293T cells expressing the Gq-coupled AT1 angiotensin receptor detecting a response to agonist concentration as low as 10 pmol/L. Compared to the wild type InsP3 sensor, the mutant sensors showed an improved off-rate, enabling a more rapid and complete return of the signal to the resting value of InsP3 after termination of M3 muscarinic receptor stimulation by atropine. For parallel measurements of intracellular InsP3 and Ca2+ levels in BRET experiments, the Cameleon D3 Ca2+ sensor was modified by replacing its CFP with luciferase. In these experiments depletion of plasma membrane PtdIns(4,5)P2 resulted in the fall of InsP3 level, followed by the decrease of the Ca2+-signal evoked by the stimulation of the AT1 receptor. In contrast, when type-III PI 4-kinases were inhibited with a high concentration of wortmannin or a more specific inhibitor, A1, the decrease of the Ca2+-signal preceded the fall of InsP3 level indicating an InsP3-, independent, direct regulation of capacitative Ca2+ influx by plasma membrane inositol lipids. Taken together, our results indicate that the improved InsP3 sensor can be used to monitor both the increase and decrease of InsP3 levels in live cells suitable for high-throughput BRET applications.

Project description:AimConservation conflict takes place where food production imposes a cost on wildlife conservation and vice versa. Where does conservation impose the maximum cost on production, by opposing the intensification and expansion of farmland? Where does conservation confer the maximum benefit on wildlife, by buffering and connecting protected areas with a habitable and permeable matrix of crop and non-crop habitat? Our aim was to map the costs and benefits of conservation versus production and thus to propose a conceptual framework for systematic conservation planning in agricultural landscapes.LocationWorld-wide.MethodsTo quantify these costs and benefits, we used a geographic information system to sample the cropland of the world and map the proportion of non-crop habitat surrounding the cropland, the number of threatened vertebrates with potential to live in or move through the matrix and the yield gap of the cropland. We defined the potential for different types of conservation conflict in terms of interactions between habitat and yield (potential for expansion, intensification, both or neither). We used spatial scan statistics to find 'hotspots' of conservation conflict.ResultsAll of the 'hottest' hotspots of conservation conflict were in sub-Saharan Africa, which could have impacts on sustainable intensification in this region.Main conclusionsSystematic conservation planning could and should be used to identify hotspots of conservation conflict in agricultural landscapes, at multiple scales. The debate between 'land sharing' (extensive agriculture that is wildlife friendly) and 'land sparing' (intensive agriculture that is less wildlife friendly but also less extensive) could be resolved if sharing and sparing were used as different types of tool for resolving different types of conservation conflict (buffering and connecting protected areas by maintaining matrix quality, in different types of matrix). Therefore, both sharing and sparing should be prioritized in hotspots of conflict, in the context of countryside biogeography.

Dataset Information

Contributing to agricultural mix:analysis of the living standard measurement study - Integrated survey on agriculture data set.

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Contributing to agricultural mix:analysis of the living standard measurement study - Integrated survey on agriculture data set.

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