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1,071 results for “Mangroves”
Eutrophication and warming rapidly alter microbial community compositions in the mangrove sediment
GEO Series GSE190739. uncultured soil microorganism. 16 samples. Type: Other.
Monitoring Burma mangrove transcriptome changes in response to salt and osmotic stress.
GEO Series GSE7228. Bruguiera gymnorhiza. 19 samples. Type: Expression profiling by array.
Developmental defects in ectodermal appendages caused by missense mutation in edaradd gene in the nfr mangrove killifish, Kryptolebias marmoratus
GEO Series GSE273026. Kryptolebias marmoratus. 12 samples. Type: Expression profiling by high throughput sequencing.
Figure 3 in A new species of Sarcofahrtiopsis (Insecta, Diptera, Sarcophagidae) from mangrove forests in the Brazilian Amazon, with a key to species identification
Figure 3. Geographic records of Sarcofahrtiopsis.
FIGURE 7 in A new species of Cicinnus Blanchard (Lepidoptera, Mimallonidae, Cicinninae) from the mangrove ecoregions of Brazil
FIGURE 7. Map of collecting localities for Cicinnus litoralis.
Dataset: Ordered Mortality of Mangroves under Extreme Flooding in a Tropical Microtidal Estuarine Lagoon in China
<p>The field investigation was conducted in January 2012, three months after the flooding event. We established two transects near the Longxi Bridge (site A and B; Fig. 1c), where the dominant species in the study area, C. tagal, was prevalent. Each transect was divided into zones with a width of 5 meters, and in each zone, we set up three 5 × 5 square meters plots for mangrove plant surveys (Fig. 1g). Site A and Site B underwent the same surveys, differing only in the length of the transects. The relative elevation of each sample plot was measured relative to the seaward edge of the fringe forest (i.e., the elevation of the seaward edge was set to 0; Fig. 1g). Elevation data in each plot were measured using the five-point method, and the average elevation of the three plots within each zone (15 measurements in total) was calculated as the average elevation for the entire zone. In each plot, we recorded the species and health status of every tree. The health status assessment, conducted by the same author, categorized trees into four levels based on their condition: healthy, acceptable, compromised, and dead. These categories were assigned values (healthy = 3, acceptable = 2, compromised = 1, dead = 0). Trees with more than 50% fresh leaf cover were considered healthy, while those with 20-50% fresh leaf cover were deemed acceptable. Compromised trees had a fresh leaf cover between 0% and 20%, while trees without any fresh leaves were considered dead. Additionally, in the middle zone of site A, we recorded the height of each tree within three plots. Since C. tagal often grows densely, we could only measure the height of a few individuals at the edges using a height rod. Therefore, researchers were trained to estimate tree height. All height estimates were made simultaneously by the same volunteer. Additionally, we selected three healthy living individuals of C. tagal from each zone and randomly chose five branchlets from each plant to count the number of leaves and propagules. Since there were fewer than three surviving C. tagal in the lowest elevation areas, all available trees were sampled. Additionally, in areas where Avicennia marina, Rhizophora apiculata, and Scyphiphora hydrophyllacea were clustered, we recorded the height and health status of many individuals, using the same methods as for C. tagal. The number of surveyed individuals for these three species was 97, 1572, and 778, respectively.</p> <p></p>
Mapping Soil Organic Carbon in the World's Largest Arid Mangrove Forest (Indus Delta, Pakistan): A Multi-Sensor Remote Sensing and Machine Learning Approach
<p><span>Mangrove forests play a crucial role in carbon sequestration, especially in arid regions where their ability to store carbon in soil is vital for mitigating climate change. The Indus Delta in Pakistan, the world’s largest arid mangrove forest system, lacks spatially explicit data on Soil Organic Carbon (SOC) despite its importance for conservation and carbon budgeting. This study aims to establish a baseline SOC map 2020 at 10 m spatial resolution using Sentinel-1 (Synthetic Aperture Radar) and Sentinel-2 (MultiSpectral Instrument) satellite imagery, integrated with in-situ soil sampling. SOC predictions were made using a Classification and Regression Tree (CART) machine learning model within the Google Earth Engine platform, leveraging 40 predictor variables, including spectral bands and derived indices. A total of 53 topsoil (0-10 cm) samples were collected in February 2020 across the Indus Delta, and SOC was analyzed using the Walkley-Black method. The results showed an average SOC value of 65.88 Mg C ha</span><span>⁻</span><span>¹ with substantial spatial variability, ranging from 15.06 Mg C ha</span><span>⁻</span><span>¹ to 138.03 Mg C ha</span><span>⁻</span><span>¹ with a total of 0.91 Pg C. The CART model demonstrated high accuracy, with an R² of 0.95 and an RMSE of 9.18 Mg C ha</span><span>⁻</span><span>¹. However, the region faces challenges such as seawater intrusion and salinity, which threaten its ability to sequester carbon. With the first high-resolution SOC map for the Indus Delta, this study provides valuable insights for ecosystem management, conservation planning, and carbon budgeting. These findings of this study have the potential to significantly influence initiatives like REDD+ and Blue Carbon projects, which aim to enhance carbon sequestration while addressing the ecological challenges facing Pakistan’s mangroves</span></p>
Fig. 3. X in Pyrrolyl 4-quinolone alkaloids from the mangrove endophytic fungus Penicillium steckii SCSIO 41025: Chiral resolution, configurational assignment, and enzyme inhibitory activities
Fig. 3. X-ray crystallographic structures of (±)-1 3, 11, and 12.
Fig. 6 in Thiocladospolides F-J, antibacterial sulfur containing 12-membered macrolides from the mangrove endophytic fungus Cladosporium oxysporum HDN13-314
Fig. 6. Plausible biosynthetic pathways of 2–9.
Data from: Changes in swamp inundation duration control pCO2 in water over spring-neap tidal cycles in a subtropical mangrove forest
<p>These datasets were used in the article 'Changes in swamp inundation duration control pCO2 in water over spring-neap tidal cycles in a subtropical mangrove forest'. The methods used for data collection and processing are described in this article.</p>
Anti-inflammatory compounds from the mangrove endophytic fungus Amorosia sp. SCSIO 41026
GEO Series GSE207442. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.