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112 results for “mangrove forest”
Figure 2 in Sarcosaprophagous flesh flies (Diptera: Sarcophagidae) are less diverse in Amazon Forest than mangroves in Northeast Brazil: preliminary insights about environmental heterogeneity
Figure 2. Study areas on São Luís Island, Maranhão state (left and middle) and canopy cover images showing the distance between Amazon Forest and mangrove areas (right): (a) Anajatiua; (b) Maracanã; (c) Sítio Aguahy; (1) mangrove; (2) forest; (3) canopy cover images. Yellow points: traps in mangrove area; red points: traps in forest area.
Figure 1 in Sarcosaprophagous flesh flies (Diptera: Sarcophagidae) are less diverse in Amazon Forest than mangroves in Northeast Brazil: preliminary insights about environmental heterogeneity
Figure 1. Locations (Anajatiua, Maracanã and Sítio Aguahy) where sampling was performed in January/February 2016 and August/September 2017 on São Luís Island in the Brazilian state of Maranhão.
Pearl River Delta FVCOM model mangrove forests scenarios
<p>Model data presented in: De Dominicis, M., Wolf, J., van Hespen, R., Zheng, P., Hu. Z. "Mangrove forests can be an effective coastal defence in the Pearl River Delta, China", <em>Communications Earth & Environment</em> (2023).</p> <p>To explore the effects of vegetation on storm surge dynamics and currents, we used a Finite Volume Community Ocean Model implementation for the South China Sea and the Pearl River Delta and simulated Typhoon Hato (2017) one of the strongest typhoons to affect the coastal areas of the Pearl River Delta in recent decades. We numerically modelled the protection capability of the mangrove wetlands in Shenzhen Bay and in the upper estuary river branches close to Guangzhou to determine their ability to mitigate coastal flooding. Additionally, we analyzed how the effectiveness of mangroves changes under different sea level rise scenarios. </p> <p>The dataset consists of water elevation and horizontal currents for 40 model experiments (see Table 1 in De Dominicis et al, 2023).</p>
Methane emissions in a subtropical mangrove forest (Ishikaki Island, Japan)
<p>The data set provides CH<sub>4</sub> flux from buttress roots and stems of individuals of <em>Bruguiera gymnorrhiza</em> of different sizes in Ishigaki Island, Japan. It also provides CH<sub>4</sub> flux from trees and sediments over a 24-hour cycle.</p>
Data from: Habitat-dependent occupancy and movement in a migrant songbird highlights the importance of mangroves and forested lagoons in Panama and Colombia
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Predicting changes in molluscan spatial distributions in mangrove forests in response to sea-level rise
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Data from: Global patterns of tree stem growth and stand aboveground wood production in mangrove forests
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Methane emissions in a subtropical mangrove forest (Ishikaki Island, Japan)
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Figures 12-16 from: Li C, Bellis G, Wu X, LI J (2019) A new species of Nilobezzia Kieffer (Diptera, Ceratopogonidae) from the mangrove forest of Hainan Island, China. ZooKeys 893: 135-141. https://doi.org/10.3897/zookeys.893.39032
Figures 12-16 Female of Nilobezzia bamenwana sp. nov. 12 terminal four segments of abdomen, ventral view 13 spermathecae and hair tufts, ventral view 14 proboscis and palpi, anterior view 15 mandibular teeth, anterior view 16 maxillary palpus, anterior view.
Figures 1-11 from: Li C, Bellis G, Wu X, LI J (2019) A new species of Nilobezzia Kieffer (Diptera, Ceratopogonidae) from the mangrove forest of Hainan Island, China. ZooKeys 893: 135-141. https://doi.org/10.3897/zookeys.893.39032
Figures 1-11 Female of Nilobezzia bamenwana sp. nov. 1 habitus in dorsal view 2 antenna 3 midtarsus, anterior view 4 foretarsus, ventral view 5 foreleg 6 midleg 7 hind leg 8 wing 9 hind tibial comb 10 head, dorsal view 11 abdominal tergite I, dorsal view.
• Nearctic (marginally) and Neotropical Regions. Rainforest to mangrove forests. in Cyclopedidae
• Nearctic (marginally) and Neotropical Regions. Rainforest to mangrove forests.
Fig. 2 in Xyleborus bidentatus (Motschulsky, 1863), a Newly Discovered Ambrosia Beetle in Mangrove Forests of Southern Iran (Coleoptera: Curculionidae: Scolytinae)
Fig. 2. Mangrove forest, Mardu Island, Iran.
Fig. 1 in Xyleborus bidentatus (Motschulsky, 1863), a Newly Discovered Ambrosia Beetle in Mangrove Forests of Southern Iran (Coleoptera: Curculionidae: Scolytinae)
Fig. 1. Xyleborus bidentatus, dorsal (left) and lateral (right) habitus.
Fig. 5 in Xyleborus bidentatus (Motschulsky, 1863), a Newly Discovered Ambrosia Beetle in Mangrove Forests of Southern Iran (Coleoptera: Curculionidae: Scolytinae)
Fig. 5. Distribution map of Xyleborus bidentatus in Iran.
Figs. 3–4 in Xyleborus bidentatus (Motschulsky, 1863), a Newly Discovered Ambrosia Beetle in Mangrove Forests of Southern Iran (Coleoptera: Curculionidae: Scolytinae)
Figs. 3–4. Traps in mangrove forest, Mardu Island, Iran. 3) Light trap; 4) Ethanol-baited trap.
Blueflux: Terrestrial Lidar Scans of Mangrove Forests, Everglades, FL, USA, 2022-2023
This dataset contains point clouds of three-dimensional (3D) mangrove forest structure and volume collected from 10 sites in Everglades National Park, Florida. Data were collected during NASA CMS "Blueflux" campaigns in March 2022, October 2022, and March 2023. Products were acquired using a RIEGL VZ-400i terrestrial laser scanner (TLS). TLS is a non-destructive and quantitative method for in situ 3D forest structure measuring and monitoring. Data are provided in LAS (*.las) format.
CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014
This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014. The data are arranged into 144 1- by 1-km tiles.
CMS: Aboveground Biomass for Mangrove Forest, Zambezi River Delta, Mozambique
This dataset provides several estimates of aboveground biomass from various regressions and allometries for mangrove forest in the Zambezi River Delta, Mozambique. Plot level estimates of aboveground biomass are based on extensive tree biophysical measurements from field campaigns conducted in September and October of 2012 and 2013. Aboveground biomass estimates for the larger area of mangrove coverage within the delta are based on (1) the plot level data and (2) canopy structure data derived from airborne LiDAR surveys in 2014. The high-resolution canopy height model for the delta region derived from the airborne LiDAR data is also included.
Greenness Trends and Carbon Stocks of Mangrove Forests Across Mexico, 2001-2015
This dataset provides estimates of greenness trends, above- and belowground carbon stocks, and climate variables of the persistent mangrove forests on the coasts of Mexico (PMFM) at a 1 km resolution from 2001 through 2015. Data are available as one-time estimates or across the temporal range; typically as monthly summaries. One-time estimates of aboveground carbon and soil organic carbon stocks for the PMFM derived from existing sources are provided. Also included are the monthly mean normalized difference vegetation index (NDVI) from MOD13A3 used to derive greenness trends, monthly mean air temperature, and total monthly precipitation from Daymet for 2001-2015 across the PMFM. Other files include the distribution and coverage of PMFM across Mexico. Distributions are provided as four categories of PMFM: (1) Arid mangroves with Surface Water as main input, along the Gulf of California and Pacific Coast (ARsw); (2) humid mangroves with surface water input along the Pacific Coast (HUsw-Pa); (3) humid mangroves with surface water input along the coast of the Gulf of Mexico (HUsw-Gf); (4) humid mangroves with groundwater input along the Gulf of Mexico and Caribbean Sea (HUgw). These data provide a baseline for national monitoring programs, carbon accounting models, and greenness trends in coastal wetlands.
CMS: Mangrove Forest Cover Extent and Change across Major River Deltas, 2000-2016
This dataset provides estimates of mangrove extent for 2016, and mangrove change (gain or loss) from 2000 to 2016, in major river delta regions of eight countries: Bangladesh, Gabon, Jamaica, Mozambique, Peru, Senegal, Tanzania, and Vietnam. For mangrove extent, a combination of Landsat 8 OLI, Sentinel-1 C-SAR, and Shuttle Radar Topography Mission (SRTM) elevation data were used to create country-wide maps of mangrove landcover extent at a 30-m resolution. For mangrove change, the global mangrove map for 2000 (Giri et al., 2010) was used as the baseline. Normalized Difference Vegetation Indices (NDVI) were calculated for every cloud- and shadow-free pixel in the Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI collection and used to create an NDVI anomaly from 2000 to 2016. Areas of change (loss or gain) occurred at the extremes of the cumulative anomalies.
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.