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72 results for “monoculture”
Arbuscular mycorrhizal symbiosis increases P uptake and productivity of mixtures of maize varieties compared to monocultures
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Data from: Disease-free monoculture farming by fungus-growing termites
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Data from: Invasive plants accelerate nitrogen cycling: evidence from experimental woody monocultures
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Monoculture species green leaf total N and delta 15N: e141: BioCON : Biodiversity, Elevated CO2, and N Enrichment
BioCON (Biodiversity, CO2, and Nitrogen) is an ecological experiment started in 1997 at the University of Minnesota's Cedar Creek Ecosystem Science Reserve. BioCON's goal is to explore the ways in which plant communities will respond to three environmental changes that are known to be occurring on a global scale: increasing nitrogen deposition, increasing atmospheric CO2, and decreasing biodiversity. Why Biodiversity, CO2, and Nitrogen? While there are many uncertainties in global change biology, there are also some well documented facts. Some of these are: 1. The amount of carbon dioxide (CO2) in the atmosphere is rising. Since the industrial revolution, the CO2 concentration in the atmosphere has increased from approximately 275 parts per million (ppm) to about 378 ppm today. This has been largely the result of fossil fuel burning. It is expected that CO2 levels will continue to rise, and that by the year 2050 these levels will be approximately 550 ppm. CO2 is the raw material for photosynthesis and is known to affect plant growth and development. 2. The amount of nitrogen moving through terrestrial ecosystems has increased in the recent past. While natural "background" levels of nitrogen fixation have remained constant, human additions to the system through fertilizer production and fossil fuel use have increased dramatically. Nitrogen is a key nutrient for plant growth and plays a critical role in plant community structure and composition in many environments. 3. Biodiversity levels are falling. While the research and data are not as complete as they are for CO2 and nitrogen, data indicate that the number of species globally, is being reduced. Perhaps more important for ecosystem function, diversity levels on local to regional scales have fallen due to land use change, biotic invasion and many other drivers. While much is known about how each of these factors affects ecosystem functioning, many questions remain. There is also little data on how these issues affe
Do diverse cover crop mixtures perform better than monocultures? A systematic review
<p>We conducted a systematic review that synthesizes a growing body of cover crop mixture research. The extracted data was analyzed to assess, for seven metric categories, whether cover crop mixtures can perform better than their constituent species when planted alone. Searching three databases, we identified 27 studies which compared cover crop mixtures (containing at least three species) to all their constituent species. The studies contained 119 sampled cover crop plantings that met our eligibility criteria. From these, we extracted 243 full comparisons of the best‐performing mixture and best‐performing monoculture for the selected metrics. Dataset S1 contains the best monoculture versus best mixture comparisons. Dataset S2 contains cover crop planting and sampling dates. Dataset S3 contains cover crop treatment coefficient of variation information. Dataset S4 contains cover crop treatment seeding rate information for studies where a non-substitutive design was used. </p>
Data from: Relationships between plant traits, soil properties and carbon fluxes differ between monocultures and mixed communities in temperate grassland
1. The use of plant traits to predict ecosystem functions has been gaining growing attention. Aboveground plant traits, such as leaf nitrogen (N) content and specific leaf area (SLA), have been shown to strongly relate to ecosystem productivity, respiration, and nutrient cycling. Further, increasing plant functional trait diversity has been suggested as a possible mechanism to increase ecosystem carbon (C) storage. However, it is uncertain whether belowground plant traits can be predicted by aboveground traits, and if both above- and belowground traits can be used to predict soil properties and ecosystem-level functions. 2. Here, we used two adjacent field experiments in temperate grassland to investigate if above- and belowground plant traits are related, and whether relationships between plant traits, soil properties and ecosystem C fluxes (i.e., ecosystem respiration and net ecosystem exchange) measured in potted monocultures could be detected in mixed field communities. 3. We found that certain shoot traits (e.g., shoot N and C, and leaf dry matter content) were related to root traits (e.g., root N, root C:N, and root dry matter content) in monocultures, but such relationships were either weak or not detected in mixed communities. Some relationships between plant traits (i.e., shoot N, root N and/or shoot C:N) and soil properties (i.e., inorganic N availability and microbial community structure) were similar in monocultures and mixed communities, but they were more strongly linked to shoot traits in monocultures and root traits in mixed communities. Structural equation modelling showed that above- and belowground traits and soil properties improved predictions of ecosystem C fluxes in monocultures, but not in mixed communities on the basis of community-weighted mean traits. 4. Synthesis: Our results from a single grassland habitat detected relationships in monocultures between above- and belowground plant traits, and between plant traits, soil properties and ecosystem C fluxes. However, these relationships were generally weaker or different in mixed communities. Our results demonstrate that while plant traits can be used to predict certain soil properties and ecosystem functions in monocultures, they are less effective for predicting how changes in plant species composition influence ecosystem functions in mixed communities.
A comparison of growth, structure and diversity of mixed species and monoculture reforestation systems in the Philippines
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Data from: Effects of spatial plant-soil feedback heterogeneity on plant performance in monocultures
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Data from: Relationships between plant traits, soil properties and carbon fluxes differ between monocultures and mixed communities in temperate grassland
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Do diverse cover crop mixtures perform better than monocultures? A systematic review
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Gene expression profile of control or shEphB6-depleted D2.0R-EGFP cells in monoculture or cocultured with AT1-like cells
GEO Series GSE162439. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profile at single cell level of in vitro monoculture and co-culture cells of ovarian clear cell carcinoma (OCCC) [OCCC_scRNAseq_invitro]
GEO Series GSE224333. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Gene expression of LNCaP cells grown in polyethlene glycol-based hydrogels alone (monocultures) and grown with human osteoblasts as tissue engineered bone (co-culture) with the presence of synthetic a
GEO Series GSE44143. Homo sapiens. 24 samples. Type: Expression profiling by array.
Gene expression in human corneal epithelial cells (hCECs) with different post-mortem intervals and cultivated in monoculture or used for human tissue‐engineered corneas (hTECs)
GEO Series GSE185459. Homo sapiens. 16 samples. Type: Expression profiling by array.
DRG-CSC co-culture tissue engineered model, CSCs monoculture model and DRG monoculture model
GEO Series GSE179020. Homo sapiens; Gallus gallus. 12 samples. Type: Expression profiling by high throughput sequencing.
Gene Expression Profiling of Listeria monocytogenes in monoculture and in co-culture state in the presence of Bacillus subtilis both as planktonic cells and in biofilms.
GEO Series GSE27936. Listeria monocytogenes J0161. 8 samples. Type: Expression profiling by array.
Gene expression of H. parainfluenzae in monoculture and coculture with S. mitis
GEO Series GSE158845. Streptococcus mitis; Haemophilus parainfluenzae. 4 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profiles of human iPSC-derived microglia in monoculture and in co-culture with isogenic iPSC-derived neural cells
GEO Series GSE243370. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Acidosis-induced gene expression regulation in human epithelial cells, fibroblasts and aortic vascular smooth muscle cells (in monoculture)
GEO Series GSE220788. Homo sapiens. 33 samples. Type: Expression profiling by high throughput sequencing.
Acidosis-induced gene expression regulation in rat cells (in monoculture)
GEO Series GSE220789. Rattus norvegicus. 23 samples. Type: Expression profiling by high throughput sequencing.
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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.