Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
38
datasets available to search
ShareScore release 0.9.0
Dataset results
38 results for “riverscape”
Data from: Riverscape genomics of a threatened fish across a hydroclimatically heterogeneous river basin
Open the record for dataset details and reuse information.
Data from: Riverscape genetics in brook lamprey: genetic diversity is less influenced by river fragmentation than by gene flow with the anadromous ecotype
Open the record for dataset details and reuse information.
Data from: Fine-scale population structure and riverscape genetics of brook trout (Salvelinus fontinalis) distributed continuously along headwater channel networks
Open the record for dataset details and reuse information.
Data from: Riverscape genetics identifies replicated ecological divergence across an Amazonian ecotone
Open the record for dataset details and reuse information.
Data from: Stream hierarchy defines riverscape genetics of a North American desert fish
Open the record for dataset details and reuse information.
Riverscape properties contribute to the origin and structure of a hybrid zone in a Neotropical freshwater fish
Open the record for dataset details and reuse information.
Data from: Comparative riverscape genetics reveals reservoirs of genetic diversity for conservation and restoration of Great Plains fishes.
Open the record for dataset details and reuse information.
Dendritic prioritization through spatial stream network modeling informs targeted management of Himalayan riverscapes under brown trout invasion
<p>With the concept of 'riverscapes' long pending to be acknowledged in the 'landscape-centric' legislative framework of Himalayan nations, conservation of native riverine species stays practically unheeded. This necessitates urgent prioritization of stream networks to conserve the lotic taxa under invasion pressures. Himalayan riverscapes are pervaded with the invasive-exotic brown trout <i>Salmo trutta</i>,<i> </i>posing serious threats to the co-occurring native, the snow trout <i>Schizothorax richardsonii</i>. Using intensive surveys (218.7km) and geostatistical stream network models (n=537), we contrasted snow trout in two stream networks with and without invasives, for assessing differences in their spatial distribution. Our models indicate invasion-induced relegations of natives from the river mainstem into headwaters, with large sections of mainstem occupied by invasives. Furthermore, a concerningly small percentage of potential habitat left for natives to occupy in the mainstem is threatened, where a 100% overlap of native and invasive trout distributions is predicted. With a higher presence probability for the natives in headwaters of invaded watershed as compared to the non-invaded watershed, we highlight the headwater streams as<b> </b>potential refugia for the natives under invasion.</p> <p><i>Synthesis and Applications: </i>Our approach of basin-scale dendritic prioritization provides immediate management solutions to tackle brown trout invasion threats in Himalaya. We inform decisions on delineation of headwaters as invasion refugia for native fish, with assisted recovery of their fragmented populations in the river mainstems through targeted management of invasives</p>
Comparative riverscape genomics of the rainbow darter (Etheostoma caeruleum) in glaciated and unglaciated environments
<p>Periodic glaciation during the Quaternary period shaped the contemporary riverscape and distribution of freshwater fishes in the Mississippi River drainage of central North America. The rainbow darter (Etheostoma caeruleum) is a member of this ichthyofauna and has a disjunct distribution in glaciated and unglaciated environments west of the Mississippi River. Based on glacial history of the region there are different expectations on the observed spatial genetic structure of populations in these environments. The aim of this study was to utilize genome-wide SNP data to compare the population genomic structure of the rainbow darter in river networks with disparate glacial histories; the Volga River in the glaciated upper Mississippi River basin and the Meramec River in the unglaciated Ozark Plateau. Individuals were sampled from localities within each river system at distances dictated by the organismal life history and habitat preferences. Riverscape analyses were performed on three datasets: total combined localities of both rivers and one for each river independently. The results revealed a lasting influence of historic glaciation on the population genomic structure of rainbow darter populations. There was evidence of population expansion into the glaciated northern region following glacial retreat. The population genetic signature within the Volga River did not fit expectations of the stream hierarchy model, but revealed a pattern of repeated colonization and extirpation due to cyclic glaciation. The population within the unglaciated Meramec River adhered to the stream hierarchy model, with a directional order of genetic diversity based on the life history and habitat preferences of the species. These results demonstrate the importance of considering the geologic and climatic history of a region as well as the life history of an organism when interpreting spatial genetic patterns.</p>
Comparative riverscape genomics of the rainbow darter (Etheostoma caeruleum) in glaciated and unglaciated environments
Open the record for dataset details and reuse information.
Data from: Riverscape genetics identifies replicated ecological divergence across an Amazonian ecotone
Open the record for dataset details and reuse information.
Dendritic prioritization through spatial stream network modeling informs targeted management of Himalayan riverscapes under brown trout invasion
Open the record for dataset details and reuse information.
Data from: A unified model for optimizing riverscape conservation
1.Spatial prioritization tools provide a means of finding efficient trade-offs between biodiversity protection and the delivery of ecosystem services. Although a large number of prioritization approaches have been proposed in the literature, most are specifically designed for terrestrial systems. When applied to river ecosystems, they often fail to adequately account for the essential role that landscape connectivity plays in maintaining both biodiversity and ecosystem services. This is particularly true of longitudinal connectivity, which in many river catchments is highly altered by the presence of dams, stream-road crossings, and other artificial structures. 2.We propose a novel framework for coordinating river conservation and connectivity restoration. As part of this, we formulate an optimization model for deciding which subcatchments to designate for ecosystem services and which to include in a river protected area (RPA) network, while also deciding which existing river barriers to remove in order to maximize longitudinal connectivity within the RPA network. In addition to constraints on the size and makeup of the RPA network, the model also considers the suitability of sites for conservation, based on a biological integrity index, and connectivity to multiple habitat types. We demonstrate the usefulness of our approach using a case study involving four managed river catchments located in Hungary. 3.Results show that large increases in connectivity-weighted habitat can be achieved through targeted selection of barrier removals and that the benefits of barrier removal are strongly depend on RPA network size. We find that (i) highly suboptimal solutions are produced if habitat conservation planning and connectivity restoration are done separately and (ii) RPA acquisition provides substantially greater marginal benefits than barrier removal given limited resources. 4.Synthesis and applications. Finding a balance between conservation and ecosystem services provision should give more consideration to connectivity restoration planning, especially in multi-use riverscapes. We present the first modelling framework to directly integrate and optimize river conservation and connectivity restoration planning. This framework can help conservation managers to account better for connectivity, resulting in more effective catchment scale maintenance of biological integrity and ecosystem services delivery.
Data from: Quantifying habitat use of migratory fish across riverscapes using space-time isotope models
1.Migratory animals pose difficult challenges to conservation and management because identifying critical habitats used throughout their lives is rarely possible. Endogenous tracers (e.g., isotope ratios) recorded in sequentially growing biogenic tissues, however, represent a potential source of unique insights at the more elusive temporal and spatial scales central to understanding the ecology of mobile species. To this end, a general probabilistic framework has emerged that quantitatively compares predictive models of isotopic variation across landscapes (called isoscapes) to the isotopic composition recorded in a biological tissue to determine the provenance and movements of animals throughout their lives. 2.Although this spatially continuous approach to isotope‐based geographic assignment is becoming more common across taxa and ecosystems, adopting this framework to take advantage of serial isotope records stored within sequentially growing biogenic tissues (e.g., teeth or otoliths) is less common. 3.Here, we construct a novel space‐time isotope model of provenance (STIMP) that determines the habitat use through time of migratory fish across river basins. To do so, this model integrates: strontium isotope (87Sr/86Sr) ratios across a riverscape, the serial records of 87Sr/86Sr within otoliths, habitat geomorphology, and the directional movement patterns of fish through river networks. 4.To illustrate an application of the model, we applied it to a published dataset from Chinook salmon (Oncorhynchus tshawytscha) harvested in 2011 during a coastal fishery in Bristol Bay, Alaska, U.S.A. Using this model, we show how individuals exploit an array of habitat types to achieve their juvenile growth prior to ocean migration, and that the intensity of habitat use among habitat types across the basin shifts spatially over the course of freshwater residence (e.g., from headwaters to migration corridors). The STIMP presented here integrates diverse information sources to reveal the cryptic juvenile movement patterns of a highly migratory species, providing new insights critical to their conservation. This general framework is applicable to any migratory taxa that use isotopically heterogeneous landscapes during their lives and record such variation in sequentially growing biogenic tissues.
Data from: A unified model for optimizing riverscape conservation
Open the record for dataset details and reuse information.
Data from: Quantifying habitat use of migratory fish across riverscapes using space-time isotope models
Open the record for dataset details and reuse information.
Soundscape and riverscape dataset of Gregoire stream, located in southern Québec (2017)
<p>Abstract: Data were collected in the summer 2017 in a second order stream of 1150 meter long with the objective to evaluate the overlap between hydromorphological and acoustical habitat features at high spatial resolution within a stream. This dataset contains 593 sample sites that measured underwater acoustic profile in term of decibel (ref: 1uPa) per 1 hertz frequency (from 1Hz to 22000Hz), water depth and velocity, stream width, primary and secondary substrate and habitat type.</p> <p>Method: The study was conducted in Gregoire Stream, a second-order stream in southern Quebec, Canada (46°05'40''N, 71°25'58''W). The area has a rain-snow regime characterized by peak water flows in spring and low flows in summer. We delineated a reach of 1150 m in length characterized by a flat low-flow section at the upstream end (stream distance = 1150 m) and a series of waterfalls at the downstream end (stream distance = 0 m), near to the confluence of Gregoire Stream and the Bagot River. The reach was crossed by a road which separated two zones differing in slope and riparian vegetation; a downstream zone having steeper slope and forest cover and an upstream zone having shallower slope and mostly shrub cover.</p> <p>The measure of hydromorphological habitat descriptors included water velocity (m s-1), water depth, stream width (cm), and primary and secondary substrate dominance. These variables were measured in 50 2.5-m sections. The sections were randomly selected without replacement from a uniform distribution over the section identifiers, on for occasions. The same set of variables was also measured in sections where fish were caught (with electrofishing). Water depth was measured at the center of the section and stream width across the wet streambed. In each section, mean water velocity was measured (Global Water Flow Probe model FP111) by slowly moving the probe up and down the water column continuously for 40 seconds. We assessed the dominant and sub-dominant wet substrates using the Wentworth granulometric scale (Wentworth 1922). In addition to hydromorphological measurements, stream habitat units were categorized using the classification system of Bisson et al. (1982), distinguishing six habitat types: pool, glide, run, riffle, cascade, and waterfall base. The length of each habitat unit along the reach was measured to the nearest 0.5 m, yielding a measure of the length of each unit.</p> <p>For the underwater soundscape, we recorded one 10-second underwater audio clip in each 2.5-m stream section immediately after we had collected hydromorphological measurements (water velocity, water depth, stream width, substrate type). We ensured by this procedure a close correspondence between the acoustical and the hydromorphological variables in time and space.</p> <p>Underwater sounds were recorded along the stream reach using a H1 hydrophone powered by a PA4 amplifier (Aquarian Scientific, Anacortes, USA) and connected to a digital recorder (H2n Recorder, Zoom, Tokyo, Japan). A total of 593 10-second audio clips were recorded (16-bit WAV format at a sampling rate of 44.1 kHz) at a depth of 5 cm below the water surface. Each audio clip was listened with earphones to ensure that the hydrophone was not rubbing on hard surfaces while recording. The recording system has a maximum input of 10 V (rms) and a rated sensitivity of -190 dB re 1 V/µPa over the flat frequency-response range 10–3,000 Hz. Above specifications were used to obtain referenced sound pressure level (SPL) (dB re 1 µPa) with the PAMGuide functions (Merchant et al. 2015). For each audio clip, the frequency spectrum averaged through time was calculated to obtain referenced SPL values in 1-Hz frequency bands over the 0.1-10 KHz range. This procedure yielded a total of 22049 dB values per audio clip.</p>
Riverscape dataset of Gregoire stream, located in southern Québec (2017)
<p>abstract: Data were collected in the summer 2017 in a second order stream with the objective to draw an hydromorphological map thru the entire stream reach (1150 meter). To do to this, the stream was characterized from its habitat types. This dataset contains the location of each habitat type presents along the stream. Six habitat types were used to characterize the stream hydromorphology (based on the Bisson classification). Waterfall base, cascade, riffle, run, glide and pool.</p> <p>Method: The study was conducted in Gregoire Stream, a second-order stream in southern Quebec, Canada (46°05'40''N, 71°25'58''W). The area has a rain-snow regime characterized by peak water flows in spring and low flows in summer. We delineated a reach of 1150 m in length characterized by a flat low-flow section at the upstream end (stream distance = 1150 m) and a series of waterfalls at the downstream end (stream distance = 0 m), near to the confluence of Gregoire Stream and the Bagot River. The reach was crossed by a road which separated two zones differing in slope and riparian vegetation; a downstream zone having steeper slope and forest cover and an upstream zone having shallower slope and mostly shrub cover. Hydromorphologic habitat features were categorized in habitat units using the classification system of Bisson et al. (1982). Six habitat types were found: pool, glide, run, riffle, cascade, and waterfall base. We measured the length of each habitat unit along the reach to the nearest 0.5 m, yielding a measure of the length of each unit.</p> <p>The entire stream reach was visually mapping after its habitat types at a precision of 0.5 meter. The characterization was performed using the classification system of Bisson et al. (1982), distinguishing six habitat types: pool, glide, run, riffle, cascade, and waterfall base. Results gave a serie of habitat unit along the stream reach with sometimes two different lateral habitats units.</p>
ScienceDex guides
Understand access before you commit
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.