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1,868 results for “Spatial Data”
Data from: Lateralization in alpha-band oscillations predicts the locus and spatial distribution of attention
Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8–13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target's location, while on others it contained no spatial information. When the target's location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target's location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex.
Data from: Impact of spatial variation of a crucial prey, the molecricket, on hoopoe territory occupancy and reproduction
Direct benefits accrued from securing a territory of sufficient quality are important determinants of individual fitness and population persistence. Food supply is one of the main factors of animal territory quality, with spatial and temporal variation in prey availability largely dictating reproductive output and thus population dynamics. In a Swiss hoopoe population, molecrickets Gryllotalpa gryllotalpa, the most profitable prey locally, can constitute most of the food biomass delivered to chicks by parents. We first investigated the impact of molecricket prey on hoopoes' fitness-related traits by quantifying the spatial variation in the food allocation pattern of both male and female parents to chicks across the whole population range; and second, analysed the impact of this prey on current reproduction and, using a 11 yr dataset, on the temporal occupancy rate of each territory. We found considerable but spatially repeatable variation, over the years, of molecricket biomass in the diet provisioned to chicks. This spatial heterogeneity in chicks' diet composition was mirrored both in the history of territory occupancy (2002–2012) and in current reproductive success (2012). Territories with a greater biomass of molecrickets in chicks' diet produced more fledglings in better body condition. Yet, these effects on current reproduction were exclusively demonstrated for male parents, corroborating that paternal provisioning patterns play a predominant role in hoopoe reproductive success. This study demonstrates how a single, very profitable prey species might affect spatial variation in territory settlement and individual reproductive success in a regionally endangered bird species, with potential consequences for its population dynamics and persistence.
Data from: The spatial segregation patterns of sharks from Western Australia
The extent to which sharks segregate by size and sex determines the population structure and the scale at which populations should be managed. We summarized 20 years of fisheries-dependent and independent sampling to define the spatial patterns of size and sexual segregation for sharks in Western Australia. Carcharhinus obscurus and C. plumbeus showed a large-scale (more than 1000 km) latitudinal gradient in size. Large individuals occurred predominantly in the northwest and north whereas smaller individuals occurred predominantly in the southwest and south. Mustelus antarcticus and Furgaleus macki showed strong sexual segregation at very large scales. Females occurred predominantly in the west and southwest whereas the proportion of males in catches substantially increased in the southeast. The populations of other shark species did not show sex and size segregation patterns at very large scales; most species, however, showed varying degrees of segregation when data were analysed at a smaller scale. These findings highlight the importance of matching the scale of observation to the scale of the phenomenon observed. As many shark species are highly mobile, if sampling is opportunistic and constrained both temporally and spatially, the observed segregation patterns may not be representative of those at the population level, leading to inaccurate scientific advice.
Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower
Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among-year variation (environmental stochasticity) are well understood, the effects of among-site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10-year demographic monitoring study, and quantified vital rate variation among sites and years using generalized linear models. I incorporated vital rate functions using this variation into integral projection models for stochastic and spatially heterogeneous environments. I also explored the effects of temporal and spatial autocorrelation, by exploring model predictions over the range of possible values for temporal autocorrelation and local seed dispersal. Vital rates varied more among years than among sites. However, environmental stochasticity and spatial heterogeneity had similar magnitude effects on population dynamics. These effects were also qualitatively different: environmental stochasticity reduced population growth rates relative to the average, whereas spatial heterogeneity increased population growth rates. Spatial autocorrelation and negative temporal autocorrelation led to higher population growth rates, although environmental stochasticity still reduced growth rates for all autocorrelation values, and spatial heterogeneity increased growth rates for all autocorrelation values. Some form of autocorrelation would be necessary for model projections to match observed population trends. Synthesis. Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long-term population dynamics.
Data from: Environmental conditions affect spatial genetic structures and dispersal patterns in a solitary rodent
The study of the spatial distribution of relatives in a population under contrasted environmental conditions provides critical insights into the flexibility of dispersal behaviour and the role of environmental conditions in shaping population relatedness and social structure. Yet few studies have evaluated the effects of fluctuating environmental conditions on relatedness structure of solitary species in the wild. The aim of this study was to determine the impact of interannual variations in environmental conditions on the spatial distribution of relatives [spatial genetic structure (SGS)] and dispersal patterns of a wild population of eastern chipmunks (Tamias striatus), a solitary rodent of North America. Eastern chipmunks depend on the seed of masting trees for reproduction and survival. Here, we combined the analysis of the SGS of adults with direct estimates of juvenile dispersal distance during six contrasted years with different dispersal seasons, population sizes and seed production. We found that environmental conditions influences the dispersal distances of juveniles and that male juveniles dispersed farther than females. The extent of the SGS of adult females varied between years and matched the variation in environmental conditions. In contrast, the SGS of males did not vary between years. We also found a difference in SGS between males and females that was consistent with male-biased dispersal. This study suggests that both the dispersal behaviour and the relatedness structure in a population of a solitary species can be relatively labile and change according to environmental conditions.
Data from: Spatial variation in Allee effects influences patterns of range expansion
Allee effects are thought to slow range expansion and contribute to stable range boundaries. Recent studies have shown Allee effects to vary spatiotemporally due to influences of environmental heterogeneity on population processes. Gradients in Allee effects might occur as a species' range approaches suboptimal conditions while expanding into new territory. Allee effects could exhibit patchiness if drivers of positive density dependence (e.g., mate finding rates) are influenced by habitat patchiness. However, theoretical studies have largely assumed Allee effects to be spatially constant. The goal of this study was to evaluate how spatiotemporal patterns of range expansion respond to spatial variations in Allee effects. We simulated spread in landscapes that differed in the spatial configuration and range of Allee thresholds. We compared spread with a constant Allee effect to spread in landscapes where the Allee threshold varied along a gradient or in a patchy fashion. Landscape configuration affected patterns of range expansion when Allee thresholds were near or exceeded the number of colonizing immigrants. In gradient landscapes, spread decelerated as the range edge approached higher Allee thresholds. In patchy landscapes, spread advanced quickly through areas with lower Allee thresholds and stalled in areas with higher Allee thresholds. Both focal and neighboring locations influencing spread. Spatial variation in Allee effects may be an underappreciated source of heterogeneity in patterns of range expansion. When Allee effects vary, spread estimates based on a spatially averaged Allee threshold may not accurately predict realized rates of spread. Our findings suggest that spread can occur despite generally high Allee thresholds if Allee thresholds are low in a subset of patches. This result has negative implications for controlling the spread of invasive species, but it also suggests range shifts by native species in response to climate change may be possible with even sparsely distributed refugia from Allee effects.
Data from: A cryptic Allee effect: spatial contexts mask an existing fitness–density relationship
Current theories predict that Allee effects should be widespread in nature, but there is little consistency in empirical findings. We hypothesized that this gap can arise from ignoring spatial contexts (i.e. spatial scale and heterogeneity) that potentially mask an existing fitness–density relationship: a 'cryptic' Allee effect. To test this hypothesis, we analysed how spatial contexts interacted with conspecific density to influence the fertilization rate of the freshwater mussel Margaritifera laevis. This sessile organism has a simple fertilization process whereby females filter sperm from the water column; this system enabled us to readily assess the interaction between conspecific density and spatial heterogeneity (e.g. flow conditions) at multiple spatial levels. Our findings were twofold. First, positive density-dependence in fertilization was undetectable at a population scale (approx. less than 50.5 m2), probably reflecting the exponential decay of sperm density with distance from the sperm source. Second, the Allee effect was confirmed at a local level (0.25 m2), but only when certain flow conditions were met (slow current velocity and shallow water depth). These results suggest that spatial contexts can mask existing Allee effects.
Data from: Spatial averaging and disturbance lead to high productivity in aquatic metacommunities
Dispersal in heterogeneous ecosystems, such as coastal metacommunities, is a major driver of diversity and productivity. According to theory, both species richness and spatial averaging shape a unimodal relationship of productivity with dispersal. We experimentally tested the hypothesis that disturbances acting on local patches would buffer the loss of productivity at high dispersal by preventing synchronized species oscillations. To simulate these disturbances, our experimental assemblages involved species that self-organized in isolation under three inflow pulsing frequencies, where hydraulic displacement and nutrient loading affected assemblage diversity and composition. At steady-state, the emerging isolated assemblages were connected at three levels of dispersal creating three metacommunities of different connectivity. Consistent with theory, as dispersal increased, species richness in the metacommunity declined; productivity however remained high. This occurred because the most productive species in our study (which dominated the isolated patch of intermediate inflow pulsing frequency) dominated all three patches (low, intermediate and high inflow pulsing frequencies) after dispersal commenced in our metacommunities. This experimental result provides empirical support for the mechanism of spatial averaging. Furthermore, disturbances, in the form of localized pulsed inflows, prevented population oscillation synchrony caused by homogenization. Overall, our observations suggest that localized environmental fluctuations and the identity of species seem to be more influential than dispersal in shaping the diversity and composition of phytoplankton assemblages and stabilizing productivity.
Data from: Genomic region detection via Spatial Convex Clustering
Several modern genomic technologies, such as DNA-Methylation arrays, measure spatially registered probes that number in the hundreds of thousands across multiple chromosomes. The measured probes are by themselves less interesting scientifically; instead scientists seek to discover biologically interpretable genomic regions comprised of contiguous groups of probes which may act as biomarkers of disease or serve as a dimension-reducing pre-processing step for downstream analyses. In this paper, we introduce an unsupervised feature learning technique which maps technological units (probes) to biological units (genomic regions) that are common across all subjects. We use ideas from fusion penalties and convex clustering to introduce a method for Spatial Convex Clustering, or SpaCC. Our method is specifically tailored to detecting multi-subject regions of methylation, but we also test our approach on the well-studied problem of detecting segments of copy number variation. We formulate our method as a convex optimization problem, develop a massively parallelizable algorithm to find its solution, and introduce automated approaches for handling missing values and determining tuning parameters. Through simulation studies based on real methylation and copy number variation data, we show that SpaCC exhibits significant performance gains relative to existing methods. Finally, we illustrate SpaCC's advantages as a pre-processing technique that reduces large-scale genomics data into a smaller number of genomic regions through several cancer epigenetics case studies on subtype discovery, network estimation, and epigenetic-wide association.
Data from: Spatial heterogeneity of tree diversity changes in montane forests under climate warming
<p>Many studies reported biotic change along a continental warming gradient. The temporal and spatial change of tree diversity and their sensitivity to climate warming might differ from region to region. however, understanding of the variation among studies with regard to the magnitude of such biotic changes is minimal, especially for montane ecosystems. To better understand spatial heterogeneity and temporal dynamics of mountain trees community change under climate warming over the past four decades. We re-surveyed and recorded all tree species from 107 long-term monitoring plots since 1974 in 2017 to study the changes of tree community composition of montane forests in the Giant Panda National Park. Our results showed that spatial differences were found in tree species diversity changes in response to climate warming over the past four decades. Tree species richness and abundance of montane forests increased over time in all our study area, except Liangshan (LS), especially in XiaoXiangLing with the highest warming rate. However, beta diversity underwent a significantly higher change rate at LS than in other mountains which indicated that plant species that do not belong to these four mountains entered LS in those year. Moreover, the beta diversities of tree between sample plots in the LS regions were homogenized. So, LS may become risk regions under continuing climatic warming, and should thus receive priority protection in the next conservation plan of the Giant Panda National Park (GPNP). We provide a explanation for the large variation among studies in warming-related biotic changes and recommend that the GPNP should implement a regional-specific conservation policy to strengthen conservation in at-risk regions (i.e., LS) under climate warming.</p>
Data from: Fine-scale spatial genetic structure across the species range reflects recent colonization of high elevation habitats in silver fir (Abies alba Mill.)
<p class="western"><span>Variation in genetic diversity across species ranges has long been recognized as highly informative for assessing populations' resilience and adaptive potential. The spatial distribution of genetic diversity within populations, referred to as fine-scale spatial genetic structure (FSGS), also carries information about recent demographic changes, yet it has rarely been connected to range scale processes. We studied eight silver fir (<i>Abies alba </i>Mill.<i>)</i> population pairs (sites), growing at high and low elevations, representative of the main genetic lineages of the species. A total of 1368 adult trees and 540 seedlings were genotyped using 137 and 116 single nucleotide polymorphisms (SNPs), respectively. Sites revealed a clear east-west isolation-by-distance pattern consistent with the post-glacial colonization history of the species. Genetic differentiation among sites (<i>F</i><sub>CT</sub>=0.148) was an order of magnitude greater than between elevations within sites (<i>F</i><sub>SC</sub>=0.031), nevertheless high elevation populations consistently exhibited a stronger FSGS. Structural equation modeling revealed that elevation and, to a lesser extent, post-glacial colonization history, but not climatic and habitat variables, were the best predictors of FSGS across populations. These results suggest that high elevation habitats have been colonized more recently across the species range. Additionally, paternity analysis revealed a high reproductive skew among adults and a stronger FSGS in seedlings than in adults, suggesting that FSGS may conserve the signature of demographic changes for several generations. Our results emphasize that spatial patterns of genetic diversity within populations provide information about demographic history complementary to non-spatial statistics, and could be used for genetic diversity monitoring, especially in forest trees.</span></p>
Data from: Comparative analysis of 2D and 3D distance measurements to study spatial genome organization
The spatial organization of genomes is non-random, cell-type specific, and has been linked to cellular function. The investigation of spatial organization has traditionally relied extensively on fluorescence microscopy. The validity of the imaging methods used to probe spatial genome organization often depends on the accuracy and precision of distance measurements. Imaging-based measurements may either use 2 dimensional datasets or 3D datasets which include the z-axis information in image stacks. Here we compare the suitability of 2D vs 3D distance measurements in the analysis of various features of spatial genome organization. We find in general good agreement between 2D and 3D analysis with higher convergence of measurements as the interrogated distance increases, especially in flat cells. Overall, 3D distance measurements are more accurate than 2D distances, but are also more susceptible to noise. In particular, z-stacks are prone to error due to imaging properties such as limited resolution along the z-axis and optical aberrations, and we also find significant deviations from unimodal distance distributions caused by low sampling frequency in z. These deviations are ameliorated by significantly higher sampling frequency in the z-direction. We conclude that 2D distances are preferred for comparative analyses between cells, but 3D distances are preferred when comparing to theoretical models in large samples of cells. In general and for practical purposes, 2D distance measurements are preferable for many applications of analysis of spatial genome organization.
Data from: Grazing and nitrogen addition restructure the spatial heterogeneity of soil microbial community structure and enzymatic activities
<p>1. In grassland ecosystems, large herbivorous animal grazing activity and increasing nitrogen deposition strongly alters microbial community structure and function. Understanding the effects of grazing and nitrogen addition on the spatial heterogeneity in soil microbial community structure, enzymatic activities and the underlying mechanisms are crucial for making better predictions of soil organic matter dynamics and nutrient cycling. </p> <p>2. We examined the spatial heterogeneity of soil microbial community structure and enzymatic activity associated with changes in soil microclimate, soil characteristics, plant biomass and soil nutrient responses to grazing and nitrogen addition using a manipulative experiment with control (CK), grazing (G), nitrogen addition (N) and grazing plus nitrogen addition (NG) treatments in a <i>Leymus chinensis </i>meadow steppe, in northeastern China. </p> <p>3. The results demonstrated that soil microbial community structure and enzymatic activities showed a high level of spatial dependence [C/(C + C0)≥0.9] in the CK plot. G, N and NG treatments not only reduced the spatial variability ofsoil microbial community structure and enzymatic activities, but also reshaped the spatial links between enzymes activities and microbial community structure. Litter biomass, soil temperature and soil nutrients (soil dissolved inorganic nitrogen or soil dissolved organic carbon) explained 21-27% of the spatial variability of soil microbial community structure in the CK treatment and pH was the strongest driver for the spatial variability of soil enzymatic activities. Meanwhile, the homogenization in soil water content induced by the N addition treatment was a determinant of the reduction in spatial heterogeneity of the microbial community structure. The combination of soil physicochemical properties (bulk density, soil pH and soil dissolved inorganic nitrogen), soil temperature and root biomass explained 32-43% of the spatial variability of the microbial community structure in the G treatment, and N and G treatments had additive effects on the spatial heterogeneity of total PLFAs by homogenizing root biomass. Plant biomass and microbial community structure were the major drivers for the spatial heterogeneity of enzymatic activities under G, N and NG. In NG, the change in spatial variability of enzymatic activities was dominated by N addition. Regardless of grazing, N addition facilitated the spatial correlation between microbial community structure and enzyme activities. </p> <p>4. Overall, our results revealed the drivers of soil microbial community structure and enzymatic activities spatial pattern shift due to grazing and N addition, highlighting the role that spatial variability in soil microbial community structure and enzymatic activities has on the <i>L. chinensis</i> meadow steppe.</p>
Supplementary material 5 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
MaxEnt Supplementary Info
Supplementary material 4 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
Moran's I Correlograms
Supplementary material 3 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
Sampled PUD occurrence
Supplementary material 2 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
InVEST model configuration
Supplementary material 1 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
Sites used for validation
Replication data for "Spatial Resolution in Inverse Problems: The EZIE satellite mission"
<p>Pandas dataframe contain synthetic measurements of an EZIE satellite.</p>
Data Repository for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin"
<p>Data for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin". This repository contains all the processed data used in the simulation (in "processed" folder), part of the raw data (in "raw" folder), and the SWAT simulation results (in "SWAT" folder). The code for processing the raw data, which are either provided here or publicly available online, is provided in the <a href="https://doi.org/10.5281/zenodo.8132662">code repository</a>. The links to the publicly available raw data are also provided in the code repository.</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.