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.
1,868
datasets available to search
ShareScore release 0.9.0
Dataset results
1,868 results for “Spatial Data”
Data from: How big of an effect do small dams have? Using geomorphological footprints to quantify spatial impact of low-head dams and identify patterns of across-dam variation
Longitudinal connectivity is a fundamental characteristic of rivers that can be disrupted by natural and anthropogenic processes. Dams are significant disruptions to streams. Over 2,000,000 low-head dams (<7.6 m high) fragment United States rivers. Despite potential adverse impacts of these ubiquitous disturbances, the spatial impacts of low-head dams on geomorphology and ecology are largely untested. Progress for research and conservation is impaired by not knowing the magnitude of low-head dam impacts. Based on the geomorphic literature, we refined a methodology that allowed us to quantify the spatial extent of low-head dam impacts (herein dam footprint), assessed variation in dam footprints across low-head dams within a river network, and identified select aspects of the context of this variation. Wetted width, depth, and substrate size distributions upstream and downstream of six low-head dams within the Upper Neosho River, Kansas, United States of America were measured. Total dam footprints averaged 7.9 km (3.0-15.3 km) or 287 wetted widths (136-437 wetted widths). Estimates included both upstream (mean: 6.7 km or 243 wetted widths) and downstream footprints (mean: 1.2 km or 44 wetted widths). Altogether the six low-head dams impacted 47.3 km (about 17%) of the mainstem in the river network. Despite differences in age, size, location, and primary function, the sizes of geomorphic footprints of individual low-head dams in the Upper Neosho river network were relatively similar. The number of upstream dams and distance to upstream dams, but not dam height, affected the spatial extent of dam footprints. In summary, ubiquitous low-head dams individually and cumulatively altered lotic ecosystems. Both characteristics of individual dams and the context of neighboring dams affected low-head dam impacts within the river network. For these reasons, low-head dams require a different, more integrative, approach for research and management than the individualistic approach that has been applied to larger dams.
Data from: The Urban Heat Island and its spatial scale dependent impact on survival and development in butterflies of different thermal sensitivity
Climate alteration is one of the most cited ecological consequences of urbanization. However, the magnitude of this impact is likely to vary with spatial scale. We investigated how this alteration affects the biological fitness of insects, which are especially sensitive to ambient conditions and well-suited organisms to study urbanization-related changes in phenotypic traits. We monitored temperature and relative air humidity in wooded sites characterized by different levels of urbanization in the surroundings. Using a split-brood design experiment, we investigated the effect of urbanization at the local (i.e., 200 × 200 m) and landscape (i.e., 3 × 3 km) scale on two key traits of biological fitness in two closely related butterfly species that differ in thermal sensitivity. In line with the Urban Heat Island concept, urbanization led to a 1°C increase in daytime temperature and an 8% decrease in daytime relative humidity at the local scale. The thermophilous species Lasiommata megera responded at the local scale: larval survival increased twofold in urban compared to rural sites. Urbanized sites tended to produce bigger adults, although this was the case for males only. In the woodland species Pararge aegeria, which has recently expanded its ecological niche, we did not observe such a response, neither at the local, nor at the landscape scale. These results demonstrate interspecific differences in urbanization-related phenotypic plasticity and larval survival. We discuss larval pre-adaptations in species of different ecological profiles to urban conditions. Our results also highlight the significance of considering fine-grained spatial scales in urban ecology.
Data from: Spatial variation in the relationship between performance and metabolic rate in wild juvenile Atlantic salmon
1. Maintenance metabolic rate (MR, the energy cost of self-maintenance) is linked to behavioural traits and fitness and varies substantially within populations. Despite having received much attention, the causes and consequences of this variation remain obscure. 2. Theoretically, such within-population variation in fitness-related traits can be maintained by environmental heterogeneity in selection patterns, but for MR this has rarely been tested in nature. 3. Here, we experimentally test if the relationship between MR and performance can vary spatially by assessing survival, growth rate and movement of Atlantic salmon (Salmo salar L.) juveniles from 10 family groups differing in MR (measured as egg metabolism) that were stocked in parallel across 10 tributaries of a single watershed. 4. The relationship between MR and relative survival and growth rate varied significantly among tributaries. Specifically, the effect of MR ranged from negative to positive for relative survival, whereas it was negative for growth rate. The association between MR and movement was positive and did not vary significantly among tributaries. 5. These results are consistent with a fitness cost of traits associated with behavioural dominance that varies across relatively small spatial scales (within a single watershed). More generally our results support the hypothesis that spatial heterogeneity in environmental conditions contributes to maintain within-population variation in fitness-related traits, such as MR.
Data from: Spatial heterogeneity lowers rather than increases host-parasite specialization
Abiotic environmental heterogeneity can promote the evolution of diverse resource specialists, which in turn may increase the degree of host-parasite specialization. We coevolved Pseudomonas fluorescens and lytic phage ϕ2 in spatially structured populations, each consisting of two interconnected subpopulations evolving in the same or different nutrient media (homogeneous and heterogeneous environments, respectively). Counter to the normal expectation, host-parasite specialization was significantly lower in heterogeneous compared with homogeneous environments. This result could not be explained by dispersal homogenizing populations, as this would have resulted in the heterogeneous treatments having levels of specialization equal to or greater than that of the homogeneous environments. We argue that selection for costly generalists is greatest when the coevolving species are exposed to diverse environmental conditions and that this can provide an explanation for our results. A simple coevolutionary model of this process suggests that this can be a general mechanism by which environmental heterogeneity can reduce rather than increase host-parasite specialization.
Data from: Spatial correlated games
The games are played in a two-dimensional lattice where the players interact with their neighbours. Four game-types are scrutinized by allowing the players to adopt the strategy of their best paid mate neighbour in iterated games. Particular attention is paid in the study to the effect of variable degree of correlation on Nash equilibrium strategy pairs.
Data from: The effects of spatial structure, frequency dependence and resistance evolution on the dynamics of toxin-mediated microbial invasions
Recent evidence suggests that interference competition between bacteria shapes the distribution of the opportunistic pathogen Staphylococcus aureus in the lower nasal airway of humans, either by preventing colonization or by driving displacement. This competition within the nasal microbial community would add to known host factors that affect colonization. We tested the role of toxin-mediated interference competition in both structured and unstructured environments, by culturing S. aureus with toxin-producing or nonproducing Staphylococcus epidermidis nasal isolates. Toxin-producing S. epidermidis invaded S. aureus populations more successfully than nonproducers, and invasion was promoted by spatial structure. Complete displacement of S. aureus was prevented by the evolution of toxin resistance. Conversely, toxin-producing S. epidermidis restricted S. aureus invasion. Invasion of toxin-producing S. epidermidis populations by S. aureus resulted from the evolution of toxin resistance, which was favoured by high initial frequency and low spatial structure. Enhanced toxin production also evolved in some invading populations of S. epidermidis. Toxin production therefore promoted invasion by, and constrained invasion into, populations of producers. Spatial structure enhanced both of these invasion effects. Our findings suggest that manipulation of the nasal microbial community could be used to limit colonization by S. aureus, which might limit transmission and infection rates.
Data from: Local biotic environment shapes the spatial scale of bacteriophage adaptation to bacteria
The ecological, epidemiological, and evolutionary consequences of host-parasite interactions are critically shaped by the spatial scale at which parasites adapt to hosts. The scale of interaction between hyperparasites and their parasites is likely to be influenced by the host of the parasite and potentially likely to differ among within-host environments. Here we examine the scale at which bacteriophages adapt to their host bacteria by studying natural isolates from the surface or interior of horse chestnut leaves. We find that phages are more infective to bacteria from the same tree relative to those from other trees but do not differ in infectivity to bacteria from different leaves within the same tree. The results suggest that phages target common bacterial species, including an important plant pathogen, within plant host tissues; this result has important implications for therapeutic phage epidemiology. Furthermore, we show that phages from the leaf interior are more infective to their local hosts than phages from the leaf surface are to theirs, suggesting either increased resistance of bacteria on the leaf surface or increased phage adaptation within the leaf. These results highlight that biotic environment can play a key role in shaping the spatial scale of parasite adaptation and influencing the outcome of coevolutionary interactions.
Data from: Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?
Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging.
Data from: Learning of efficient behaviour in spatial exploration through observation of behaviour of conspecific in laboratory rats
Recent studies have suggested that rodent behaviour is influenced by the behaviour of surrounding conspecifics (e.g. emotional contagion and prosocial behaviour). However, little is known about deferred imitation and complex observational learning in rats. The purpose of this study was to reveal whether rats can learn from another rat's experiences. In a maze, observer rats watched the foraging behaviour of other rats (demonstrators) and then foraged in turn. The results showed that demonstrators explored inefficiently, but observers explored more efficiently after observing inefficient exploration by the demonstrators. This observational learning probably involved the acquisition of an efficient strategy through spatial exploration.
Data from: Nitrogen addition does not reduce the role of spatial asynchrony in stabilizing grassland communities
While nitrogen (N) amendment is known to affect the stability of ecological communities, whether this effect is scale‐dependent remains an open question. By conducting a field experiment in a temperate grassland, we found that both plant richness and temporal stability of community biomass increased with spatial scale, but N enrichment reduced richness and stability at the two scales considered. Reduced local‐scale stability under N enrichment arose from N‐induced reduction in population stability, which was partly attributable to the decline in local species richness, as well as reduction in asynchronous local population dynamics across species. Importantly, N enrichment did not alter spatial asynchrony among local communities, which provided similar spatial insurance effects at the larger scale, regardless of N enrichment levels. These results suggest that spatial variability among local communities, in addition to local diversity, may help stabilise ecosystems at larger spatial scales even in the face of anthropogenic environmental changes.
Data from: Shear-induced orientational dynamics and spatial heterogeneity in suspensions of motile phytoplankton
Fluid flow, ubiquitous in natural and man-made environments, has the potential to profoundly impact the transport of microorganisms, including phytoplankton in aquatic habitats and bioreactors. Yet, the effect of ambient flow on the swimming behavior of phytoplankton has remained poorly understood, largely due to the difficulty of observing cell-flow interactions at the microscale. Here, we present microfluidic experiments where we tracked individual cells for four species of motile phytoplankton exposed to a spatially non-uniform fluid shear rate, characteristic of many flows in natural and artificial environments. We observed that medium to high mean shear rates (1 – 25 s^-1) produce heterogeneous cell concentrations in the form of regions of accumulation and regions of depletion. The location of these regions relative to the flow depends on the cells' propulsion mechanism, body shape, and flagellar arrangement, as captured by an effective aspect ratio. Species having a large effective aspect ratio accumulated in the high-shear regions, due to shear-induced alignment of the swimming orientation with the fluid streamlines. Species having an effective aspect ratio close to unity exhibited little preferential accumulation at low to moderate flow rates, but strongly accumulated in the low-shear regions under high flow conditions, potentially due to an active, behavioral response of cells to shear. These observations demonstrate that ambient fluid flow can strongly affect the motility and spatial distribution of phytoplankton and highlight the rich dynamics emerging from the interaction between motility, morphology, and flow.
Data from: Spatial discounting of food and social rewards in guppies (Poecilia reticulata).
In temporal discounting, animals trade off the time to obtain a reward against the quality of a reward, choosing between a smaller reward available sooner versus a larger reward available later. Similar discounting can apply over space, when animals choose between smaller and closer versus larger and more distant rewards. Most studies of temporal and spatial discounting in nonhuman animals use food as the reward, and it is not established whether animals trade off other preferred stimuli in similar ways. Here, we offered female guppies (Poecilia reticulata) a spatial discounting task in which we measured preferences for a larger reward as the distance to it increased relative to a closer but smaller reward. We tested whether the fish discounted reward types differently by offering subjects either food items or same-sex conspecifics as rewards. Before beginning the discounting tasks, we conducted validation tests to ensure that subjects equally valued the food and social stimuli in the quantities provided. In the discounting task, subjects switched their preferences from the larger to the smaller reward as the distance to the larger reward increased (spatial discounting), but the pattern and magnitude of discounting did not differ across the two reward types. These findings indicate that guppies show similar patterns of discounting food and social rewards in a spatial task. In an analysis of travel times, however, the fish swam faster to food rewards than to shoaling partners. This difference in travel times implies that fish temporally discounted social rewards less steeply than food rewards. Thus, reward type influences temporal discounting, suggesting a dissociation between temporal and spatial discounting. Our results illustrate how animals adjust choices and travel times depending on both the type of cost (time, distance) and benefits (food, social partners).
Data from: Spatially structured statistical network models for landscape genetics
A basic understanding of how the landscape impedes, or creates resistance to, the dispersal of organisms and hence gene flow is paramount for successful conservation science and management. Spatially structured ecological networks are often used to represent spatial landscape-genetic relationships, where nodes represent individuals or populations and resistance to movement is represented using non-binary edge weights. Weights are typically assigned or estimated by the user, rather than observed, and validating such weights is challenging. We provide a synthesis of current methods used to estimate edge weights and an overview of common model types, stressing the advantages and disadvantages of each approach and their ability to model landscape-genetic data. We further explore a set of spatial-statistical methods that provide ecologists with alternative approaches for modeling spatially explicit processes that may affect genetic structure. This includes an overview of spatial autoregressive models, with a particular focus on how correlation and partial correlation are used to represent neighborhood structure with the inverse of the covariance matrix (i.e., precision matrix). We then demonstrate how to model resistance by specifying an appropriate statistical model on the nodes, conditioned on the edge weights, through the precision matrix. This integration of network ecology and spatial statistics provides a practical analytical framework for landscape-genetic studies. The results can be used to make statistical inferences about the relative importance of individual landscape characteristics, such as the vegetative cover, hillslope, or the presence of roads or rivers, on gene flow. In addition, the R code we include allows readers to explore landscape-genetic structure in their own datasets, which will potentially provide new insights into the evolutionary processes that generated ecological networks, as well as valuable information about the optimal characteristics of conservation corridors.
Data from: Spatial distribution of nests constrains the strength of sexual selection in a warbler
In socially monogamous species, extra-pair paternity may increase the strength of inter-sexual selection by allowing males with preferred phenotypes to monopolize matings. Several studies have found relationships between male signals and extra-pair mating, but many others fail to explain variation in extra-pair mating success. A greater appreciation for the role that ecological contingencies play in structuring behavioral processes may help to reconcile contradictory results. We studied extra-pair mating in a spatial context in the common yellowthroat (Geothlypis trichas), a territorial wood warbler. Over the course of six years, we observed 158 breeding attempts by 99 males, resulting in a total of 369 nests and 520 sampled nestlings. The spatial distribution of territories varied greatly, with males having between 0 and 10 close neighbors and between 3 and 39 neighboring nestlings close enough to represent extra-pair siring opportunities. Both within-pair and extra-pair reproductive success increased with breeding density, but the opportunity for sexual selection and strength of selection varied with density. Total variance in reproductive success was highest at low density and was mostly explained by variation in within-pair success. In contrast, at high density, both within-pair and extra-pair success contributed substantially to variance in reproductive success. The relationships between plumage and extra-pair mating also varied by density; plumage was under strong sexual selection via extra-pair mating success at high density but no selection was detected at low density. Thus, ecological factors that structure social interactions can drive patterns of sexual selection by facilitating or constraining the expression of mating preferences.
Data from: Life history determines biogeographical patterns of soil bacterial communities over multiple spatial scales
The extent to which the distribution of soil bacteria is controlled by local environment versus spatial factors (e.g., dispersal, colonisation limitation, evolutionary events) is poorly understood and widely debated. Our understanding of biogeographic controls in microbial communities is likely hampered by the enormous environmental variability encountered across spatial scales and the broad diversity of microbial life histories. Here we constrained environmental factors (soil chemistry, climate, above-ground plant community) to investigate the specific influence of space, by fitting all other variables first, on bacterial communities in soils over distances from m to 102 km. We found strong evidence for a spatial component to bacterial community structure that varies with scale and organism life history (dispersal and survival ability). Geographic distance had no influence over community structure for organisms known to have survival stages, but the converse was true for organisms thought to be less hardy. Community function (substrate utilisation) was also shown to be highly correlated to community structure, but not to abiotic factors, suggesting non-stochastic determinants of community structure are important Our results support the view that bacterial soil communities are constrained by both edaphic factors and geographic distance, and further show that the relative importance of such constraints depends critically on the taxonomic resolution used to evaluate spatio-temporal patterns of microbial diversity, as well as life-history of the groups being investigated, much as is the case for macro-organisms.
Data from: Multiple processes drive genetic structure of humpback whale (Megaptera novaeangliae) populations across spatial scales
Elucidating patterns of population structure for species with complex life histories, and disentangling the processes driving such patterns, remains a significant analytical challenge. Humpback whale (Megaptera novaeangliae) populations display complex genetic structures that have not been fully resolved at all spatial scales. We generated a data set of nuclear markers for 3,575 samples spanning the seven breeding stocks and substocks found in the South Atlantic and western and northern Indian Oceans. For the total sample, and males and females separately, we assessed genetic diversity, tested for genetic differentiation between putative populations and isolation by distance, estimated the number of genetic clusters without a priori population information, and estimated rates of gene flow using maximum likelihood and Bayesian approaches. At the ocean basin scale, structure is governed by geographic distance (IBD p<0.05) and female fidelity to breeding areas, in line with current understanding of the drivers of broad-scale population structure. Consistent with previous studies, the Arabian Sea breeding stock was highly genetically differentiated (FST 0.034-0.161; p<0.01 for all comparisons). However, the breeding stock boundary between west South Africa and east Africa was more porous than expected based on genetic differentiation, cluster, and gene flow analyses. Instances of male-fidelity to breeding areas and relatively high rates of dispersal for females were also observed between the three substocks in the western Indian Ocean. This mismatch between demographic units and current management boundaries may have ramifications for assessments of the status and continued protections of populations still in recovery from commercial whaling.
Data from: Population genomic analysis suggests strong influence of river network on spatial distribution of genetic variation in invasive saltcedar across the southwestern US
Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in the invasive riparian shrub saltcedar (Tamarix L.) by analyzing 1,997 genome-wide SNP markers for 259 individuals from 25 populations collected throughout the southwestern US. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers, and founder effects during range expansion.
Data from: Aspiration-based coevolution of link weights promotes cooperation in the spatial prisoner's dilemma game
In this article, we propose an aspiration-based coevolution of link weights, and we explore how this affects the evolution of cooperation in the spatial prisoner's dilemma game. In particular, an individual will increase the weight of its link to its neighbors only if the payoff received via this interaction will exceed a pre-defined aspiration. Conversely, if the received payoff is below this aspiration, the link weight with the corresponding neighbor will be decreased. Our simulation results show that an appropriate aspiration level leads to a high-cooperation plateau, whereas a too high or a too low aspiration will impede the evolution of cooperation. We explain these findings with a comprehensive analysis of transition points and with a systematic analysis of typical configuration patterns. The presented results provide further theoretical insights with regards to the impact of different aspiration levels on cooperation in human societies.
Data from: Spatially explicit models of divergence and genome hitchhiking
Strong barriers to genetic exchange can exist at divergently selected loci, whereas alleles at neutral loci flow more readily between populations, thus impeding divergence and speciation in the face of gene flow. However, 'divergence hitchhiking' theory posits that divergent selection can generate large regions of differentiation around selected loci. 'Genome hitchhiking' theory suggests that selection can also cause reductions in average genome-wide rates of gene flow, resulting in widespread genomic divergence (rather than divergence only around specific selected loci). Spatial heterogeneity is ubiquitous in nature, yet previous models of genetic barriers to gene flow have explored limited combinations of spatial and selective scenarios. Using simulations of secondary contact of populations, we explore barriers to gene flow in various selective and spatial contexts in continuous, two-dimensional, spatially explicit environments. In general, effects of hitchhiking are strongest in environments with regular spatial patterning of starkly divergent habitat types. When divergent selection is very strong, the absence of intermediate habitat types increases the effects of hitchhiking. However, when selection is moderate or weak, regular (versus random) spatial arrangement of habitat types becomes more important than the presence of intermediate habitats per se. We also document counterintuitive processes arising from the stochastic interplay of selection, gene flow, and drift. Our results indicate that generalization of results from two-deme models requires caution and increase understanding of the genomic and geographic basis of population divergence.
Data from: Spatial detection of outlier loci with Moran eigenvector maps (MEM)
The spatial signature of microevolutionary processes structuring genetic variation may play an important role in the detection of loci under selection. However, the spatial location of samples has not yet been used to quantify this. Here, we present a new two-step method of spatial outlier detection at the individual and deme levels using the power spectrum of Moran eigenvector maps (MEM). The MEM power spectrum quantifies how the variation in a variable, such as the frequency of an allele at a SNP locus, is distributed across a range of spatial scales defined by MEM spatial eigenvectors. The first step (Moran spectral outlier detection: MSOD) uses genetic and spatial information to identify outlier loci by their unusual power spectrum. The second step uses Moran spectral randomization (MSR) to test the association between outlier loci and environmental predictors, accounting for spatial autocorrelation. Using simulated data from two published papers, we tested this two-step method in different scenarios of landscape configuration, selection strength, dispersal capacity and sampling design. Under scenarios that included spatial structure, MSOD alone was sufficient to detect outlier loci at the individual and deme levels without the need for incorporating environmental predictors. Follow-up with MSR generally reduced (already low) false-positive rates, though in some cases led to a reduction in power. The results were surprisingly robust to differences in sample size and sampling design. Our method represents a new tool for detecting potential loci under selection with individual-based and population-based sampling by leveraging spatial information that has hitherto been neglected.
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.