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1,102 results for “human use”
Genetic editing of primary human dorsal root ganglion neurons using CRISPR-Cas9
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Human dermal microvascular arterial and venous blood endothelial cells and their use in bioengineered dermo-epidermal skin substitutes in vitro and in vivo
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Spatial separation of prey from livestock facilitates coexistence of a specialized large carnivore with human land use
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Data from: Long-term human land-use change throughout Southeast Asia reshapes the distribution of suitable habitat for a human-commensal bird species
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Data from: Elephant pathway use in a human-dominated landscape
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Integrating human trail use in montane landscapes reveals larger zones of human influence for wary carnivores
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Data from: The influence of human presence and footprint on animal space use in US national parks
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Data from: Early detection of human impacts using acoustic monitoring: an example with forest elephants
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Data from: Personality trait structures across three species of Macaca, using survey ratings of responses to conspecifics and humans
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African sunbirds predominantly pollinate plants useful to humans
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De novo genome assembly of human cell line CHM13 nanopore ultra-long reads using Shasta
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High-density single-unit human cortical recordings using the Neuropixels probe
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Predicting human health from biofluid-based metabolomics using machine learning
<p>Processed input data sets as well as output files and trained health state predictive models for human diseases using metabolomics of biofluids. These data are associated with the following manuscript: 'Predicting human health from biofluid-based metabolomics using machine learning' https://doi.org/10.1101/2020.01.29.20019471</p>
Dataset: Toothbrushing Data and Analysis of its Potential Use in Human Activity Recognition Applications
<p>This is the dataset that accompanies the paper 'Dataset: Toothbrushing Data and Analysis of its Potential Use in Human Activity Recognition Applications'.</p> <p>In this paper, we describe and analyze a time-series dataset from toothbrushing activity using brush-attached and wearable sensors. The data was collected from 17 participants when they brushed their teeth over one week in 5 different locations. The dataset consists of 62 toothbrushing sessions for each of the brush-attached and wearable sensor approaches, using both electric and manual brushes. The average duration of each session is 2 minutes. One sensor device was attached to the handle of the brush while the other was worn by the participants as a wrist-watch. We collected the data from a 3-axis accelerometer and a 3-axis gyroscope at a 200 Hz sampling rate.</p> <p>Accompanying code can be found at our GitHub repository <a href="https://github.com/icl-mq/toothbrushing-dataset">https://github.com/icl-mq/toothbrushing-dataset</a>. This repository contains example code demonstrating how to process the data along with the file metadata.</p>
Human mediated land use change drives intraspecific plant trait variation
<p>In the Anthropocene, more than three quarters of ice-free land has experienced some form of human driven habitat modification, with agriculture dominating 40% of the Earth's surface. This land use change alters the quality, availability, and configuration of habitat resources, affecting the community composition of plants and insects, as well as their interactions with each other. Landscapes dominated by agriculture are known to support a lower abundance and diversity of pollinators and frequently larger populations of key herbivore pests. In turn, insect communities subsidized by agriculture may spill into remaining natural habitats with consequences for wild plants persisting in (semi) natural habitats. Adaptive responses by wild plants may allow them to persist in highly modified landscapes; yet how landscape-mediated variation in insect communities affects wild plant traits related to reproduction and defense remains largely unknown. We synthesize the evidence for plant trait changes across land use gradients and propose potential mechanisms by which landscape-mediated changes in insect communities may be driving these trait changes. Further, we present results from a common garden experiment on three wild <i>Brassica </i>species demonstrating variation in both defensive and reproductive traits along an agricultural land use gradient. Our framework illustrates the potential for plant adaptation under land use change and predicts how defense and reproduction trait expression may shift in low diversity landscapes. We highlight areas of future research into plant population and community effects of land use change.</p>
Data from: Habitat differences influence genetic impacts of human land use on the American beech (Fagus grandifolia)
Natural reforestation after regional forest clearance is a globally common land-use sequence. The genetic recovery of tree populations in these recolonized forests may depend on the biogeographic setting of the landscape, for instance whether they are in the core or in the marginal part of the species' range. Using data from 501 individuals genotyped across 7 microsatellites, we investigated whether regional differences in habitat quality affected the recovery of genetic variation in a wind-pollinated tree species, American beech (Fagus grandifolia) in Massachusetts. We compared populations in forests that were recolonized following agricultural abandonment to those in remnant forests that have only been logged in both central inland and marginal coastal regions. Across all populations in our entire study region, recolonized forests showed limited reduction of genetic diversity as only observed heterozygosity was significantly reduced in these forests (H O = 0.520 and 0.590, respectively). Within inland region, this pattern was observed, whereas in the coast, recolonized populations exhibited no reduction in all genetic diversity estimates. However, genetic differentiation among recolonized populations in marginal coastal habitat increased (F st logged = 0.072; F st secondary = 0.249), with populations showing strong genetic structure, in contrast to inland region. These results indicate that the magnitude of recovery of genetic variation in recolonized populations can vary at different habitats.
Data from: Contrasting trait assembly patterns in plant and bird communities along environmental and human-induced land-use gradients
Human-driven environmental changes can induce marked shifts in the functional structure of biological communities with possible repercussion on important ecosystem functions and services. At the same time it remains unclear to which extent these changes may differently affect various types of organisms. We investigated species richness and community functional structure of species assemblages at the landscape scale (1km2 plots) for two contrasting model taxa, i.e., plants (producers and sessile organisms) and birds (consumers and mobile organisms), along topography, climate, landscape heterogeneity, and land-use (agriculture and urbanization) gradients in a densely populated region of Switzerland. Our study revealed that agricultural and urban land uses drove marked shifts in the functional structure of biological communities compared to changes along climate and topography gradients, especially for plants, while for birds these changes were comparable. Agricultural and urban land uses enhanced divergence in traits related to resource use for birds (diet and nesting), growth forms, dispersal, and reproductive traits for plants, while it induced convergence in vegetative plant traits (plant height and leaf dry matter content). These results suggest that contrasting assembly patterns may arise within and across taxonomic groups along the same environmental gradients as result of distinct underlying processes and 'organism-specific' environmental perceptions. Our results further suggest a potential homogenization of biological communities, as well as low functional diversity and redundancy levels of bird assemblages in our human-dominated study region. This might potentially compromise the maintenance of key ecological processes under future environmental changes.
Urban herring gulls use human behavioural cues to locate food
While many animals are negatively affected by urbanisation, some species appear to thrive in urban environments. Herring gulls (<i>Larus argentatus</i>) are commonly found in urban areas and often scavenge food discarded by humans. Despite increasing interactions between humans and gulls, little is known about the cognitive underpinnings of urban gull behaviour and to what extent they use human behavioural cues when making foraging decisions. We investigated whether gulls are more attracted to anthropogenic items when they have been handled by a human. We first presented free-living gulls with two identical food objects, one of which was handled, and found that gulls preferentially pecked at the handled food object. We then tested whether gulls' attraction to human-handled objects generalises to non-food items by presenting a new sample of gulls with two non-food objects, where, again, only one was handled. While similar numbers of gulls approached food and non-food objects in both experiments, they did not peck at handled non-food objects above chance levels. These results suggest that urban gulls generally show low levels of neophobia, but that they use human handling as a cue specifically in the context of food. These behaviours may contribute to gulls' successful exploitation of urban environments.
Data from: Fencing solves human‐wildlife conflict locally but shifts problems elsewhere: a case study using functional connectivity modelling of the African elephant
1. Fencing is one of the commonest methods for mitigating human-wildlife conflicts. At the same time, fencing is considered to be of one of the most pressing emerging threats to conservation globally. Although fences act as barriers and eventually can cause population isolation and fragmentation, it is challenging to quantitatively predict the possible consequences fences have for wildlife. 2. Here, we model how fencing designed to mitigate human-elephant conflict (HEC) on the Borderlands between Kenya and Tanzania will affect functional connectivity and movement corridors for African elephants. Specifically, we (1) model functional landscape connectivity integrating natural and anthropogenic factors; (2) predict seasonal movement corridors used by elephants in non-protected areas; and (3) evaluate whether fencing in one area can potentially intensify human-wildlife conflicts elsewhere. 3. We used GPS movement and remote sensing data to develop monthly step-selection functions to model functional connectivity. For future scenarios, we used a currently ongoing fencing project designed for human-elephant conflict mitigation within the study area. We modelled movement corridors using least-cost path and circuit theory methods, evaluated their predictive power and quantified connectivity changes resulting from the planned fencing. 4. Our results suggest that fencing will not cause landscape fragmentation and will not change functional landscape connectivity dramatically. However, fencing will lead to a loss of connectivity locally and will increase the potential for HEC in new areas. We estimated that wetlands important for movement corridors will be more intensively used by the elephants, which may also cause problems of overgrazing. Seasonal analysis highlighted an increasing usage of non-protected lands in the dry season and equal importance of the pinch point wetlands for preserving overall function connectivity. 5. Synthesis and applications. Fencing is a solution to small-scale HEC problems, but will not solve the issue at a broader scale. Moreover, our results highlight that it may intensify the conflicts and overuse of habitat patches in other areas, thereby negating any conservation benefits. If fencing is employed on a broader scale, then it is imperative that corridors are integrated within the protected area network to ensure local connectivity of affected species.
Data from: Using human vision to detect variation in avian coloration: How bad is it?
Assessing variation in animal coloration is difficult as animals differ in their visual system properties. This has led some to propose that human vision can never be used to evaluate coloration, yet many studies have a long history of relying on human vision. To reconcile these views, we compared the reflectance spectra of preserved avian plumage elements with two measures that are humans biased: RGB values from digital photographs and the corresponding reflectance spectra from a field guide. We measured 73 plumage elements across 14 bird species. The field guide reflectance spectra were drastically different from that of the actual birds, particularly for blue elements. However, principal components analyses on all three data sets indicated remarkably similar data structure. We conclude that human vision can detect much of the variation in coloration in the visible range, providing fodder for subsequent studies in ecology, evolution, behavior, and visual ecology.
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.