Soil carbon in the Jena Experiment (all blocks Main Experiment up to 30cm depth, year 2002)

This data set contains soil carbon measurements (Organic carbon, inorganic carbon, and total carbon; all measured in dried soil samples) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Stratified soil sampling was performed before sowing in April 2002. Five independent samples per plot were taken using a split tube sampler with an inner diameter of 4.8 cm (Eijkelkamp Agrisearch Equipment, Giesbeek, the Netherlands). Soil samples were dried at 40°C and then segmented to a depth resolution of 5 cm giving six depth subsamples per core. All samples were analyzed independently and averaged values per depth layer are reported. Soil samples were passed through a sieve with a mesh size of 2 mm. Rarely present visible plant remains were removed using tweezers. Total carbon concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). We measured inorganic carbon concentration by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon.

Soil carbon in the Jena Experiment (all blocks Main Experiment up to 30cm depth, year 2004)

This data set contains soil carbon measurements (Organic carbon, inorganic carbon, and total carbon; all measured in dried soil samples) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Stratified soil sampling was performed in April 2004 to a depth of 30 cm. Three samples per plot were taken using a split tube sampler with an inner diameter of 4.8 cm (Eijkelkamp Agrisearch Equipment, Giesbeek, the Netherlands). Sampling locations were less than 30 cm apart from sampling locations in 2002. Soil samples were segmented into 5 cm depth segments in the field (resulting in six depth layers) and made into composite samples per depth. Subsequently, samples were dried at 40°C. All soil samples were passed through a sieve with a mesh size of 2 mm. Because of much higher proportions of roots in the soil, samples in years after 2002 were further sieved to 1 mm according to common root removal methods. No additional mineral particles were removed by this procedure. Total carbon concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s**-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). We measured inorganic carbon concentration by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon.

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 15cm depth, year 2008)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m of the mineral soil from each of the experimental plots in March and October 2008. In October 2008, also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled. Samples of the soil cores per plot (subplots in case of the management experiment) were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, AutoAnalyzer, Seal, Burgess Hill, United Kingdom).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 15cm depth, year 2006)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m of the mineral soil from each of the experimental plots in March 2006. In October 2006 also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled. Measurements from the management experiment are separated into 0 to 0.08 m and 0.08 to 0.15 m. Samples of the soil cores per plot (subplots in case of the management experiment) were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, AutoAnalyzer, Seal, Burgess Hill, United Kingdom).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 15cm depth, year 2007)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m of the mineral soil from each of the experimental plots in March and October 2007. In March and in October 2007 also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details below) were sampled. Samples of the soil cores per plot (subplots in case of the management experiment) were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, AutoAnalyzer, Seal, Burgess Hill, United Kingdom).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 30cm depth, year 2003)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m and 0.15 to 0.3 m of the mineral soil from each of the experimental plots in March, June, and October 2003. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).

Increase in soil organic carbon by agricultural intensification in northern China

Acknowledgements. This research was supported by National Natural Science Foundation of China (no. 31370527 and 31261140367) and the National Science and Technology Support Program of China (no. 2012BAD14B01-2). The authors gratefully thank the Huantai Agricultural Station for providing of the Soil Fertility Survey data. We also thank Zheng Liang from China Agricultural University for the soil sampling and analysis in 2011. Thanks are extended to Jessica Bellarby for helpful discussion and suggestions.

Soil chemical attributes and leaf nutrients of Pacovan banana under two cover crops.

Banana is one of the most consumed fruits in the world, which is grown in most tropical countries. The objective of this work was to evaluate the main attributes of soil fertility in a banana crop under two cover crops and two root development locations. The work was conducted in Curaçá, BA, Brazil, between October 2011 and May 2013, using a randomized block design in split plot with five repetitions. Two cover crops were assessed in the plots, the cover 1 consisting of Pueraria phaseoloid es, and the cover 2 consisting of a crop mix with Sorghum bicolor, Ricinus commun is L., Canavalia ensiform is, Mucuna aterrima and Zea mays, and two soil sampling locations in the subplots, between plants in the banana rows (location 1) and between the banana rows (location 2). There were significant and independent effects for the cover crop and sampling location factors for the variables organic matter, Ca and P, and significant effects for the interaction between cover crops and sampling locations for the variables potassium, magnesium and total exchangeable bases. The cover crop mix and the between-row location presented the highest organic matter content. Potassium was the nutrient with the highest negative variation from the initial content and its leaf content was below the reference value, however not reducing the crop yield. The banana crop associated with crop cover using the crop mix provided greater availability of nutrients in the soil compared to the coverage with tropical kudzu.

The influence of temperature and introduction point on the detection of Rhyzopertha dominica in stored grain

The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

Country-scale carbon accounting of the vegetation and mineral soils of Finland

The increase in global temperature has been attributed to increased atmospheric concentrations of greenhouse gases (GHG), mainly that of CO2. The threat of severe and complex socio-economic and ecological implications of climate change have initiated an international process that aims to reduce emissions, to increase C sinks, and to protect existing C reservoirs. The famous Kyoto protocol is an offspring of this process. The Kyoto protocol and its accords state that signatory countries need to monitor their forest C pools, and to follow the guidelines set by the IPCC in the preparation, reporting and quality assessment of the C pool change estimates. The aims of this thesis were i) to estimate the changes in carbon stocks vegetation and soil in the forests in Finnish forests from 1922 to 2004, ii) to evaluate the applied methodology by using empirical data, iii) to assess the reliability of the estimates by means of uncertainty analysis, iv) to assess the effect of forest C sinks on the reliability of the entire national GHG inventory, and finally, v) to present an application of model-based stratification to a large-scale sampling design of soil C stock changes. The applied methodology builds on the forest inventory measured data (or modelled stand data), and uses statistical modelling to predict biomasses and litter productions, as well as a dynamic soil C model to predict the decomposition of litter. The mean vegetation C sink of Finnish forests from 1922 to 2004 was 3.3 Tg C a-1, and in soil was 0.7 Tg C a-1. Soil is slowly accumulating C as a consequence of increased growing stock and unsaturated soil C stocks in relation to current detritus input to soil that is higher than in the beginning of the period. Annual estimates of vegetation and soil C stock changes fluctuated considerably during the period, were frequently opposite (e.g. vegetation was a sink but soil was a source). The inclusion of vegetation sinks into the national GHG inventory of 2003 increased its uncertainty from between -4% and 9% to ± 19% (95% CI), and further inclusion of upland mineral soils increased it to ± 24%. The uncertainties of annual sinks can be reduced most efficiently by concentrating on the quality of the model input data. Despite the decreased precision of the national GHG inventory, the inclusion of uncertain sinks improves its accuracy due to the larger sectoral coverage of the inventory. If the national soil sink estimates were prepared by repeated soil sampling of model-stratified sample plots, the uncertainties would be accounted for in the stratum formation and sample allocation. Otherwise, the increases of sampling efficiency by stratification remain smaller. The highly variable and frequently opposite annual changes in ecosystem C pools imply the importance of full ecosystem C accounting. If forest C sink estimates will be used in practice average sink estimates seem a more reasonable basis than the annual estimates. This is due to the fact that annual forest sinks vary considerably and annual estimates are uncertain, and they have severe consequences for the reliability of the total national GHG balance. The estimation of average sinks should still be based on annual or even more frequent data due to the non-linear decomposition process that is influenced by the annual climate. The methodology used in this study to predict forest C sinks can be transferred to other countries with some modifications. The ultimate verification of sink estimates should be based on comparison to empirical data, in which case the model-based stratification presented in this study can serve to improve the efficiency of the sampling design.

磁处理对红壤酶活性和牧草(苏丹草)幼苗生长的影响

In 0.15T and 0.35T(Tesla) magnetic fields, soil breathing intensity, activities of invertase and phosphatase were improved, but activity of urease was inhibited. After applying magnetized coal ash to red soil, the rate of germination of Sudan grass was increased, growth of seedlings was speeded up, and activity of polyphenol oxidase was decreased.

黄土丘陵林区开垦地土壤侵蚀强度时间变化研究

以黄土丘陵林区 1 0 a径流泥沙观测资料为基础 ,分析了林地开垦后不同侵蚀年限情况下土壤侵蚀强度的变化。结果发现 ,随侵蚀年限的增长 ,土壤侵蚀强度呈明显的增长趋势 ,平均每年约有 1 0 mm的土层被侵蚀掉 ,到侵蚀的第 1 0 a时 ,已有 1 0 0 .81 mm的土层被侵蚀掉 ,相当于林地土壤的 A层大部分遭到流失。土壤侵蚀强度的增加 ,土壤质量的下降 ,土壤性状的恶化 ,更促使侵蚀程强度的加剧

黄土丘陵林区开垦地人为加速侵蚀与土壤物理力学性质的时间变化

以子午岭土壤侵蚀与生态环境演变观测站长年观测的径流泥沙资料为基础 ,分析了林地及其开垦地不同侵蚀年限土壤的颗粒组成、>0 .2 5 mm水稳性团粒含量、抗剪强度和容重等土壤物理力学性质与土壤侵蚀强度的关系。研究结果表明 ,>0 .2 5 mm水稳性团粒含量对土壤侵蚀强度影响最大 ,其偏相关系数为 0 .972 8,其次为土壤的粗粉粒含量和抗剪强度。最后对 >0 .2 5 mm水稳性团粒含量和抗剪强度与土壤侵蚀强度的关系进行了分析 ,表明林地开垦后侵蚀第 1年和第 7年为土壤侵蚀强度加剧的转折点 ,说明了森林植被在防治黄土高原土壤侵蚀方面的作用。

黄土丘陵林区开垦地土壤抗冲性的时间变化研究

以黄土丘陵林区 10a径流泥沙观测资料为基础 ,进行土壤抗冲试验 ,分析了林地及其开垦后不同年限土壤的抗冲性能。结果表明 ,林地具有很强的抗冲性能 ,一旦被开垦后 ,随侵蚀年限的增长 ,土壤的抗冲性呈减弱趋势 ,在 3L/min流量下 ,土壤冲刷量从侵蚀 1a的 4.0 1g/L增大到侵蚀 10a的 2 5 .5 1g/L ,加剧了土壤侵蚀发展。相关分析表明 ,土壤的抗剪强度对抗冲性影响最大 ,其次为水稳性团粒和有机质含量。因此 ,退耕还林、恢复和重建植被 ,改善土壤侵蚀环境 ,提高土壤抗冲性 ,能有效地防治土壤侵蚀。

Compositonal Analysis of Potentially harmful Elements in Soils: Implications for Epidemiology and Kidney Disease

A substantial proportion of aetiological risks for many cancers and chronic diseases remain unexplained. Using geochemical soil and stream water samples collected as part of the Tellus Project studies, current research is investigating naturally occurring background levels of potentially toxic elements (PTEs) in soils and stream sediments and their possible relationship with progressive chronic kidney disease (CKD). The Tellus geological mapping project, Geological Survey Northern Ireland, collected soil sediment and stream water samples on a grid of one sample site every 2 km2 across the rural areas of Northern Ireland resulting in an excess of 6800 soil sampling locations and more than 5800 locations for stream water sampling. Accumulation of several PTEs including arsenic, cadmium, chromium, lead and mercury have been linked with human health and implicated in renal function decline. The hypothesis is that long-term exposure will result in cumulative exposure to PTEs and act as risk factor(s) for cancer and diabetes related CKD and its progression. The ‘bioavailable’ fraction of total PTE soil concentration depends on the ‘bioaccessible’ proportion through an exposure pathway. Recent work has explored this bioaccessible fraction for a range of PTEs across Northern Ireland. In this study the compositional nature of the multivariate geochemical PTE variables and bioaccessible data is explored to augment the investigation into the potential relationship between PTEs, bioaccessibility and disease data.