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110 results for “Soil structure”
Effects of past and present-day landscape structure on forest soil microorganisms
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Soil structure changes under reduced tillage and cover cropping enhance carbon mineralization in Mediterranean croplands
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Data from: Positive plant diversity effects on soil microbial drought resistance are linked to variation in labile carbon and microbial community structure
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Data from: Effects of straw return on soil carbon and nitrogen pools and on the diversity of microbial structures and functions
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Contrasting effects of deadwood and gaps on the trophic structure of forest soil microarthropods
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Biochar and nitrogen fertilizer promote rice yield by altering soil enzyme activity and microbial community structure
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Data for: Spatial structure within root systems moderates stability of Arbuscular Mycorrhizal mutualism and plant-soil feedbacks
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Trophic structure and origin of resources of soil macrofauna in the salt marsh of the Wadden Sea: a stable isotope (15N,13C) study
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Soil nitrogen: Interactive Effects of Fertility and Distribution on Plant Community Diversity and Structure
There are four levels of nitrogen, corresponding to treatments A, C, F and G in E001, applied at the same time as in that experiment. For a description of fertilizer added to E052, see file fertilization details. There are four levels of soil disturbance designated 1, 2, 3 and 4. Level 1: undisturbed Level 2: 1 pass with a 7 HP Honda rear-tined rototiller with the elevator set to till to a depth of 9 inches Level 3: 2 passes or however many required to produce about 50% bare ground Level 4: 3 passes or however many required to produce 100% bare ground. This requires 3 passes in some plots but 5 or 6 in others. In addition, all woody vegetation not destroyed by tilling is cut at the base. Rototilling is applied in late April. Each fertilization treatment receives each disturbance treatment, for a total of sixteen treatments. There are four replicates of each of the sixteen treatments. In addition, the four extreme ends (lowest N, lowest disturbance; highest N, lowest disturbance, etc. ) are replicated an additional ten times. Treatments are applied in a completely randomized design. Each of the 104 plots is 5m x 5m. Measurements taken at E052 will include: 1) species abundances, 2) community biomass allocation to leaves/roots/stems/flowers, 3) above and below ground net primary production and 4) rates of nitrogen mineralization. For a list of treatments, see the treatment layouts in file trmte52. The plots in E052 are enclosed by a fence to exclude mammalian herbivores. Galvanized welded-wire hardware cloth with 6mm x 6mm openings was buried to a depth of 50cm. Additional hardware cloth extends 60cm above the ground and poultry netting extends to 2m above the ground. In 1990, ten plots of each of four treatments (N1D1, N1D4, N4D1, N4D4, where N is the level of nitrogen added and D is the disturbance treatment) were randomly selected for the competition experiment. The above and belowground effects of neighbors on transplanted grass seedlings were measured using three
Soil nitrate and ammonium: Interactive Effects of Fertility and Distribution on Plant Community Diversity and Structure
There are four levels of nitrogen, corresponding to treatments A, C, F and G in E001, applied at the same time as in that experiment. For a description of fertilizer added to E052, see file fertilization details. There are four levels of soil disturbance designated 1, 2, 3 and 4. Level 1: undisturbed Level 2: 1 pass with a 7 HP Honda rear-tined rototiller with the elevator set to till to a depth of 9 inches Level 3: 2 passes or however many required to produce about 50% bare ground Level 4: 3 passes or however many required to produce 100% bare ground. This requires 3 passes in some plots but 5 or 6 in others. In addition, all woody vegetation not destroyed by tilling is cut at the base. Rototilling is applied in late April. Each fertilization treatment receives each disturbance treatment, for a total of sixteen treatments. There are four replicates of each of the sixteen treatments. In addition, the four extreme ends (lowest N, lowest disturbance; highest N, lowest disturbance, etc. ) are replicated an additional ten times. Treatments are applied in a completely randomized design. Each of the 104 plots is 5m x 5m. Measurements taken at E052 will include: 1) species abundances, 2) community biomass allocation to leaves/roots/stems/flowers, 3) above and below ground net primary production and 4) rates of nitrogen mineralization. For a list of treatments, see the treatment layouts in file trmte52. The plots in E052 are enclosed by a fence to exclude mammalian herbivores. Galvanized welded-wire hardware cloth with 6mm x 6mm openings was buried to a depth of 50cm. Additional hardware cloth extends 60cm above the ground and poultry netting extends to 2m above the ground. In 1990, ten plots of each of four treatments (N1D1, N1D4, N4D1, N4D4, where N is the level of nitrogen added and D is the disturbance treatment) were randomly selected for the competition experiment. The above and belowground effects of neighbors on transplanted grass seedlings were measured using three
Soil pH: Interactive Effects of Fertility and Distribution on Plant Community Diversity and Structure
There are four levels of nitrogen, corresponding to treatments A, C, F and G in E001, applied at the same time as in that experiment. For a description of fertilizer added to E052, see file fertilization details. There are four levels of soil disturbance designated 1, 2, 3 and 4. Level 1: undisturbed Level 2: 1 pass with a 7 HP Honda rear-tined rototiller with the elevator set to till to a depth of 9 inches Level 3: 2 passes or however many required to produce about 50% bare ground Level 4: 3 passes or however many required to produce 100% bare ground. This requires 3 passes in some plots but 5 or 6 in others. In addition, all woody vegetation not destroyed by tilling is cut at the base. Rototilling is applied in late April. Each fertilization treatment receives each disturbance treatment, for a total of sixteen treatments. There are four replicates of each of the sixteen treatments. In addition, the four extreme ends (lowest N, lowest disturbance; highest N, lowest disturbance, etc. ) are replicated an additional ten times. Treatments are applied in a completely randomized design. Each of the 104 plots is 5m x 5m. Measurements taken at E052 will include: 1) species abundances, 2) community biomass allocation to leaves/roots/stems/flowers, 3) above and below ground net primary production and 4) rates of nitrogen mineralization. For a list of treatments, see the treatment layouts in file trmte52. The plots in E052 are enclosed by a fence to exclude mammalian herbivores. Galvanized welded-wire hardware cloth with 6mm x 6mm openings was buried to a depth of 50cm. Additional hardware cloth extends 60cm above the ground and poultry netting extends to 2m above the ground. In 1990, ten plots of each of four treatments (N1D1, N1D4, N4D1, N4D4, where N is the level of nitrogen added and D is the disturbance treatment) were randomly selected for the competition experiment. The above and belowground effects of neighbors on transplanted grass seedlings were measured using three
Vegetation structure and soil chemistry on Hog Island, Northampton Co. Virginia, May/June 2012
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Data from: The bacterial community structure and functional profile in the heavy metal contaminated paddy soils,surrounding a nonferrous smelter in South Korea
The pollution of agricultural soils by the heavy metals affects the productivity of the land and has an impact on the quality of the surrounding ecosystems. The present study investigated the bacterial community structure in the heavy metal contaminated sites along a smelter and a distantly located paddy field to elucidate the factors that are related to the alterations of the bacterial communities under the conditions of heavy metal pollution. Among the study sites, the bacterial communities in the soil did not show any significant differences in their richness and diversity. The soil bacterial communities at the three study sites were distinct from one another at each site, possessing a distinct set of bacterial phylotypes. Among the study sites, significant changes were observed in the abundances of the bacterial phyla and genera. The variations in the bacterial community structure were mostly related to the general soil properties at the phylum level, while at the finer taxonomic levels, the concentrations of arsenic (As) and lead (Pb) were the significant factors, affecting the community structure. The relative abundances of the genera Desulfatibacillum and Desulfovirga were negatively correlated to the concentrations of As, Pb, and cadmium (Cd) in the soil, while the genus Bacillus was positively correlated to the concentrations of As and Cd. According to the results of the prediction of bacterial community functions, the soil bacterial communities of the heavy metal polluted sites were characterized by the more abundant enzymes, involved in DNA replication and repair, translation, transcription, and the nucleotide metabolism pathways, while the amino acid and lipid metabolism, as well as the biodegradation potential of xenobiotics, were reduced. Our results showed that the adaptation of the bacterial communities to the heavy metal contamination was predominantly attributed to the replacement process, while the changes in community richness were linked to the variations in the soil pH values.
Data from: Soil abiotic variables are more important than Salicaceae phylogeny or habitat specialization in determining soil microbial community structure
Predicting the outcome of interspecific interactions is a central goal in ecology. The diverse soil microbes that interact with plants are shaped by different aspects of plant identity, such as phylogenetic history and functional group. Species interactions may also be strongly shaped by abiotic environment, but there is mixed evidence on the relative importance of environment, plant identity, and their interactions in shaping soil microbial communities. Using a multi-factor, split-plot field experiment, we tested how hydrologic context, and three facets of Salicaceae plant identity - habitat specialization, phylogenetic distance, and species identity - influence soil microbial community structure. Analysis of microbial community sequencing data with generalized dissimilarity models showed that abiotic environment explained up to 25% of variation in community composition of soil bacteria, fungi, and archaea, while Salicaceae identity influenced less than 1% of the variation in community composition of soil microbial taxa. Multivariate linear models indicated that the influence of Salicaceae identity was small, but did contribute to differentiation of soil microbes within treatments. Moreover, results from a microbial niche breadth analysis show that soil microbes in wetlands have more specialized host associations than soil microbes in drier environments - showing that abiotic environment changed how plant identity correlated with soil microbial communities. This study demonstrates the predominance of major abiotic factors in shaping soil microbial community structure; the significance of abiotic context to biotic influence on soil microbes; and the utility of field experiments to disentangling the abiotic and biotic factors that are thought to be most essential for soil microbial communities.
Data from: Diffuse symbioses: roles of plant–plant, plant–microbe and microbe–microbe interactions in structuring the soil microbiome
A conceptual model emphasizing direct host–microbe interactions has dominated work on host-associated microbiomes. To understand plant–microbiome associations, however, broader influences on microbiome composition and functioning must be incorporated, such as those arising from plant–plant and microbe–microbe interactions. We sampled soil microbiomes associated with target plant species (Andropogon gerardii, Schizachyrium scoparium, Lespedeza capitata, Lupinus perennis) grown in communities varying in plant richness (1-, 4-, 8- or 16-species). We assessed Streptomyces antagonistic activity and analysed bacterial and Streptomyces populations via 454 pyrosequencing. Host plant species and plant richness treatments altered networks of coassociation among bacterial taxa, suggesting the potential for host plant effects on the soil microbiome to include changes in microbial interaction dynamics and, consequently, co-evolution. Taxa that were coassociated in the rhizosphere of a given host plant species often showed consistent correlations between operational taxonomic unit (OTU) relative abundance and Streptomyces antagonistic activity, in the rhizosphere of that host. However, in the rhizosphere of a different host plant species, the same OTUs showed no consistency, or a different pattern of responsiveness to such biotic habitat characteristics. The diversity and richness of bacterial and Streptomyces communities exhibited distinct relationships with biotic and abiotic soil characteristics. The rhizosphere soil microbiome is influenced by a complex and nested array of factors at varying spatial scales, including plant community, plant host, soil edaphics and microbial taxon and community characteristics.
Data from: Patterns of earthworm, enchytraeid and nematode diversity and community structure in urban soils of different ages
Annelids (Lumbricidae and Enchytraeidae) and nematodes are common soil organisms and play important roles in organic matter decomposition, nutrient cycling and creation of soil structure and porosity. However, these three groups have rarely been studied together and only few studies exist for urban soils. We studied the diversity and community composition of annelids and nematodes in soils spanning more than two centuries of urban soil development in Neuchâtel (Switzerland) and assessed the relationships 1) among these three groups and 2) between each group and environmental (physical, chemical and functional) characteristics of soils and soil age. While the groups of environmental variables were correlated (Mantel tests) no correlation was found between pairs of soil fauna groups and between each soil fauna group and environmental variables. More specifically, redundancy analyses showed that earthworm assemblages were best correlated with soil bulk density and with soil depth, the latter being positively correlated with soil age. Enchytraeid assemblages and the proportion of enchytraeid r-strategists were respectively best correlated with soil carbonate content and negatively correlated with soil age. Nematodes assemblages were best correlated with soil water content. Moreover, relationships between pairs of soil biota groups, and between each group and environmental (physical, chemical and functional) variables, varied along the soil age gradient (moving window analysis). This study provides new knowledge on urban soil biodiversity and how environmental conditions can influence soil diversity and community patterns in the urban context. The contrasted community patterns of earthworms, enchytraeids and nematodes in urban soils of different ages and their different ecological roles suggest that they represent potential complementary indicators of soil quality and functioning such as soil formation and organic matter dynamics.
Convergence in simulating global soil organic carbon by structurally different models after data assimilation
<p>This is the data for results shown in the article accepted by Global Change Biology: Convergence in simulating global soil organic carbon by structurally different models after data assimilation</p>
The success of alien plants in an arid ecosystem: Structural equation modeling reveals hidden effects of soil resources
<p> data</p>
FIGURE 5. Secondary structures for the D1–D1 in Porphyrosiphon annulatus sp. nov. (Oscillatoriales, Cyanobacteria) isolated on moist soil in Suwon, Republic of Korea
FIGURE 5. Secondary structures for the D1–D1ʹ helix (A–G) and Box-B helix (H–N) in conserved regions of the 16S–23S ITS. (A, H) Microcoleus vaginatus, (B, I) M. autumnalis, (C, J) Kamptonema formosum, (D, K) Anagnostidinema carotinosum, (E, L), A. pseudacutissimum, (F, M) Geitlerinema splendidum, (G, N) Porphyrosiphon annulatus. Species in bold represents our studied organism.
Tropical montane forest in South Asia: Composition, structure and dieback in relation to soils and topography
<p>We evaluated the composition, structure and dieback of a montane forest in relation to soils and physiography of an important biogeographic region that has been sparsely studied. Our objectives were to: 1. Describe the forest composition and structure; 2. Assess the current extent of dieback; and 3. Relate tree composition, structure, and dieback proneness to edaphic and physiographic measures. We enumerated all live and dead standing plants ≥ 3 cm diameter at breast height (DBH), in thirty 20×15 m<sup>2</sup> over story plots. We measured all regeneration <u><</u> 1m height in subplots, sampled soils and measures of physiography, and visually rated the proportion of crown die-back, and recorded standing dead trees.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.