991 resultados para SOIL NEMATODE COMMUNITY
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2010, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2013, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2008, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2002, vegetation cover was estimated only once in Septemper just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2002, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2003, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2003, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2005, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2005, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2006, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2006, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2007, vegetation cover was estimated twice in June and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2007, dead plant material was found only in a few plots. Therefore, cover of dead plant material is zero for most of the 82 plots.
Resumo:
This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is 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. In 2004, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2004, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.
Resumo:
The McMurdo Dry Valleys of Antarctica are an extreme polar desert. Mineral soils support subsurface microbial communities and translucent rocks support development of hypolithic communities on ventral surfaces in soil contact. Despite significant research attention, relatively little is known about taxonomic and functional diversity or their inter-relationships. Here we report a combined diversity and functional interrogation for soil and hypoliths of the Miers Valley in the McMurdo Dry Valleys of Antarctica. The study employed 16S rRNA fingerprinting and high throughput sequencing combined with the GeoChip functional microarray. The soil community was revealed as a highly diverse reservoir of bacterial diversity dominated by actinobacteria. Hypolithic communities were less diverse and dominated by cyanobacteria. Major differences in putative functionality were that soil communities displayed greater diversity in stress tolerance and recalcitrant substrate utilization pathways, whilst hypolithic communities supported greater diversity of nutrient limitation adaptation pathways. A relatively high level of functional redundancy in both soil and hypoliths may indicate adaptation of these communities to fluctuating environmental conditions.
Resumo:
Two-third of the terrestrial C is stored in soils, and more than 50% of soil organic C (SOC) is stored in subsoils from 30 – 100 cm. Hence, subsoil is important as a source or sink for CO2 in the global carbon cycle. Especially the stable organic carbon (OC) is stored in subsoil, as several studies have shown that subsoil OC is of a higher average age than topsoil OC. However, there is still a lack of knowledge regarding the mechanisms of C sequestration and C turnover in subsoil. Three main factors are discussed, which possibly reduce carbon turnover rates in subsoil: Resource limitation, changes in the microbial community, and changes in gas conditions. The experiments conducted in this study, which aimed to elucidate the importance of the mentioned factors, focused on two neighbouring arable sites, with depth profiles differing in SOC stocks: One Colluvic Cambisol (Cam) with high SOC contents (8-12 g kg-1) throughout the profile and one Haplic Luvisol (Luv) with low SOC contents (3-4 g kg-1) below 30 cm depth. The first experiment was designed to gain more knowledge regarding the microbial community and its influence on carbon sequestration in subsoil. Soil samples were taken at four different depths on the two sites. Microbial biomass C (MBC) was determined to identify depth gradients in relation to the natural C availability. Bacterial and fungal residues as well as ergosterol were determined to quantify changes in the in the microbial community composition. Multi-substrate-induced-respiration (MSIR) was used to identify shifts in functional diversity of the microbial community. The MSIR revealed that substrate use in subsoil differed significantly from that in topsoil and also differed highly between the two subsoils, indicating a strong influence of resource limitations on microbial substrate use. Amino sugar analysis and the ratio of ergosterol to microbial biomass C showed that fungal dominance decreased with depth. The results clearly demonstrated that microbial parameters changed with depth according to substrate availability. The second experiment was an incubation experiment using subsoil gas conditions with and without the addition of C4 plant residues. Soil samples were taken from topsoil and subsoil of the two sites. SOC losses during the incubation, were not influenced by the subsoil gas conditions. Plant-derived C losses were generally stronger in the Cam (7.5 mg g-1), especially at subsoil gas conditions, than in the Luv (7.0 mg g-1). Subsoil gas conditions had no general effects on microbial measures with and without plant residue addition. However, the contribution of plant-derived MBC to total MBC was significantly reduced at subsoil gas conditions. This lead to the conclusion that subsoil gas conditions alter the metabolism of microorganisms but not the degradation of added plant residues is general. The third experiment was a field experiment carried out for two years. Mesh bags containing original soil material and maize root residues (C4 plant) were buried at three different depths at the two sites. The recovery of the soilbags took place 12, 18, and 24 months after burial. We determined the effects of these treatments on SOC, density fractions, and MBC. The mean residence time for maize-derived C was similar at all depths and both sites (403 d). MBC increased to a similar extent (2.5 fold) from the initial value to maximum value. This increase relied largely on the added maize root residues. However, there were clear differences visible in terms of the substrate use efficiency, which decreased with depth and was lower in the Luv than in the Cam. Hence freshly added plant material is highly accessible to microorganisms in subsoil and therefore equally degraded at both sites and depths, but its metabolic use was determined by the legacy of soil properties. These findings provide strong evidence that resource availability from autochthonous SOM as well as from added plant residues have a strong influence on the microbial community and its use of different substrates. However, under all of the applied conditions there was no evidence that complex substrates, i.e. plant residues, were less degraded in subsoil than in topsoil.
Resumo:
Heterodera glycines, the soybean cyst nematode, is the major pathogen of Glycine max (soybean). Effective management of this pathogen is contingent on the use of resistant cultivars, thus screening for resistant cultivars is essential. The purpose of this research was to develop a method to assess infection of soybean roots by H. glycines with real-time quantitative Polymerase Chain Reaction (qPCR), a prelude to differentiation of resistance levels in soybean cultivars. Two experiments were conducted. In the first one, a consistent inoculation method was developed using to provide active second-stage juveniles (J2). Two-day-old soybean roots were infested with 0 and 1000 J2/mL. Twenty-four hours after infestation, the roots were surface sterilized and DNA was extracted with the DNA FastKit (MP Biomedicals, Santa Ana, CA)). For the qPCR assay, primer pair for single copy gene HgSNO, which codes for a protein involved in the production of vitamin B6, was selected for H. glycines DNA amplification within soybean roots. In the second experiment, compatible Lee 74, incompatible Peking and cultivars with different levels of resistance to H. glycines were inoculated with 0 and 1,000 J2/seedlings. Twenty-four hours post inoculation they were transplanted into pasteurized soil. Subsequently they were harvested at 1, 7, 10, 14 and 21 days post inoculation for DNA extraction. With the qPCR assay, the time needed to differentiate highly resistant cultivars from the rest was reduced. Quantification of H. glycines infection by traditional means (numbers of females produced in 30 days) is a time-consuming practice; the qPCR method can replace the traditional one and improve precision in determining infection levels.
Resumo:
Soil horizons below 30 cm depth contain about 60% of the organic carbon stored in soils. Although insight into the physical and chemical stabilization of soil organic matter (SUM) and into microbial community composition in these horizons is being gained, information on microbial functions of subsoil microbial communities and on associated microbially-mediated processes remains sparse. To identify possible controls on enzyme patterns, we correlated enzyme patterns with biotic and abiotic soil parameters, as well as with microbial community composition, estimated using phospholipid fatty acid profiles. Enzyme patterns (i.e. distance-matrixes calculated from these enzyme activities) were calculated from the activities of six extracellular enzymes (cellobiohydrolase, leucine-amino-peptidase, N-acetylglucosaminidase, chitotriosidase, phosphatase and phenoloxidase), which had been measured in soil samples from organic topsoil horizons, mineral topsoil horizons, and mineral subsoil horizons from seven ecosystems along a 1500 km latitudinal transect in Western Siberia. We found that hydrolytic enzyme activities decreased rapidly with depth, whereas oxidative enzyme activities in mineral horizons were as high as, or higher than in organic topsoil horizons. Enzyme patterns varied more strongly between ecosystems in mineral subsoil horizons than in organic topsoils. The enzyme patterns in topsoil horizons were correlated with SUM content (i.e., C and N content) and microbial community composition. In contrast, the enzyme patterns in mineral subsoil horizons were related to water content, soil pH and microbial community composition. The lack of correlation between enzyme patterns and SUM quantity in the mineral subsoils suggests that SOM chemistry, spatial separation or physical stabilization of SUM rather than SUM content might determine substrate availability for enzymatic breakdown. The correlation of microbial community composition and enzyme patterns in all horizons, suggests that microbial community composition shapes enzyme patterns and might act as a modifier for the usual dependency of decomposition rates on SUM content or C/N ratios. (C) 2015 The Authors. Published by Elsevier Ltd.
Resumo:
Microorganisms in the plant rhizosphere, the zone under the influence of roots, and phyllosphere, the aboveground plant habitat, exert a strong influence on plant growth, health, and protection. Tomatoes and cucumbers are important players in produce safety, and the microbial life on their surfaces may contribute to their fitness as hosts for foodborne pathogens such as Salmonella enterica and Listeria monocytogenes. External factors such as agricultural inputs and environmental conditions likely also play a major role. However, the relative contributions of the various factors at play concerning the plant surface microbiome remain obscure, although this knowledge could be applied to crop protection from plant and human pathogens. Recent advances in genomic technology have made investigations into the diversity and structure of microbial communities possible in many systems and at multiple scales. Using Illumina sequencing to profile particular regions of the 16S rRNA gene, this study investigates the influences of climate and crop management practices on the field-grown tomato and cucumber microbiome. The first research chapter (Chapter 3) involved application of 4 different soil amendments to a tomato field and profiling of harvest-time phyllosphere and rhizosphere microbial communities. Factors such as water activity, soil texture, and field location influenced microbial community structure more than soil amendment use, indicating that field conditions may exert more influence on the tomato microbiome than certain agricultural inputs. In Chapter 4, the impact of rain on tomato and cucumber-associated microbial community structures was evaluated. Shifts in bacterial community composition and structure were recorded immediately following rain events, an effect which was partially reversed after 4 days and was strongest on cucumber fruit surfaces. Chapter 5 focused on the contribution of insect visitors to the tomato microbiota, finding that insects introduced diverse bacterial taxa to the blossom and green tomato fruit microbiome. This study advances our understanding of the factors that influence the microbiomes of tomato and cucumber. Farms are complex environments, and untangling the interactions between farming practices, the environment, and microbial diversity will help us develop a comprehensive understanding of how microbial life, including foodborne pathogens, may be influenced by agricultural conditions.
Resumo:
OF TAFFETA AND SOIL is a collection of poetry unified through images of Argentinean and Floridian soil, flora, and fauna, and by themes of geographic and emotional dislocation, memory, and the quest for home. These images are brought forth in lyrical poems that question the growth and settling of a romantic partnership, domestic turmoil and resolution, and the constant tension between self and community. Mostly written in free verse, the collection also utilizes forms such as prose poem, haiku, and sonnet, for more formal unity. Section one chronicles and explores a romantic relationship through attraction, passion, disappointment, and self-awareness. Section two is a long poem that centers on the speaker’s continuous struggle to come to terms with her present adult life while still remembering and idealizing a homeland. Finally, the collection ends with two sections that work toward self-acceptance, forgiveness, and evolution via community, family, travel and nature.