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11 results for “riparian corridor”
Vegetation surveys in the riparian (bosque) corridor of the Middle Rio Grande valley, NM
This dataset contains vegetation cover information from 34 long-term Bosque Ecosystem Monitoring Program (BEMP) sites from 2000 – 2021. Data were collected along ten 30-m transects at each site at the centimeter scale each year in August-early October as funding and site access allowed. At the fullest extent, sites spanned 520 km of the riparian forest along the Rio Grande. The purpose of this dataset is to track plant species at sites along the Rio Grande in New Mexico. From this dataset, changes in plant species abundance, richness, and species diversity can be tracked and analyzed with ecosystem drivers such as flooding, fire, species removal/fuel reduction projects, and climate change. Species are coded using USDA Plant Database codes, allowing species information to be added to each species, including origin (native or nonnative), duration (e.g., annual, biennial, perennial), and plant type (e.g., grass, forb, vine, shrub, tree). This dataset has allowed the tracking of the ascendance of nonnatives in some sites, the recovery of natives in other sites, success or lack of success following restoration projects, and records of new species occurring in various counties and the state of New Mexico.
Data from: CO-RIP: a riparian vegetation and corridor extent dataset for Colorado River Basin streams and rivers
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Fig 7 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 7 Cross section of a floodplain ecosystem in relation to diversity of Orthoptera and anthropogenic modification of the landscape.
Fig 2 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 2 The number of identified cricket (Gryllidae) species in a riparian paddy field near Mount Fuji at differing distances from a levee (after Ichihara et al. 2014b).
Fig 3 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 3 Arakawa super levee in Tokyo. Grassland is left uncut to produce a mosaic of habitats for Orthoptera. Photo by T. Gardiner.
Fig 5 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 5 Concrete paddy levee and field along the Tama River (Fussa) providing minimal habitat for Orthoptera. Photo by T. Gardiner.
Fig 6 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 6 Gravel floodplain along the Tama River, early successional habitat for the endangered Eusphingonotusjaponicus grasshopper and Asterkantoensis. Photo by T. Gardiner.
Fig 4 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 4 Flat terrace on the riverside slope of a flood defense embankment at Kasai Rinkai Park at the mouth of the Edogawa River in Tokyo Bay. The terrace is accumulating vegetation, including Astertripolium, a rare and declining species in the Bay. Photo by T. Gardiner.
Fig 1 from: Gardiner T, Kuramoto N, Matsuba M (2019) Big in Japan: The importance of riparian corridors for Orthoptera. Journal of Orthoptera Research 28(1): 27-35. https://doi.org/10.3897/jor.28.31380
Fig 1 Grassland buffering the shoreline on Fukuura Island in Matsushima Bay, acting as a natural flood defense. Grasshoppers (Oxya spp.) were numerous in this coastal corridor. Photo by T. Gardiner.
Avian point count data from riparian corridors of protected areas in Marin County California
<p>The data set is a simplified version of avian point count data collected in Marin County, CA, USA between 1997 and 2019. Point count surveys (5 minutes) were conducted twice during the breeding season (May and June) along transects in riparian corridors within protected areas (Point Reyes National Seashore, Golden Gate National Recreation Area, Mount Tamalpais State Park, and Bolinas Lagoon Open Space Preserve). Data were collected by Point Blue Conservation Science biologists and were integrated into the National Park Service Inventory and Monitoring Program. All individuals detected at any distance were recorded during the surveys, but this simplified data set only includes the observations analyzed for this publication, specifically detections (aurally and visually) within 50 meters of each point count station for each of the fourteen species selected for analysis.</p>
Avian point count data from riparian corridors of protected areas in Marin County California
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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.