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580 results for “pattern analysis”
Meta-analysis of elevational changes in the intensity of trophic interactions: similarities and dissimilarities with latitudinal patterns
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Data from: Continental patterns of phenotypic variation along replicated urban gradients: A mega-analysis
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30 years of terrestrial insect richness patterns across elevation: What have we learned? A global meta-analysis
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Data and codes to replicate the analysis in: The spatial ecology of conflicts: Unravelling patterns of wildlife damage at multiple scales
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Data from: Explaining global variation in the latitudinal diversity gradient: meta-analysis confirms known patterns and uncovers new ones
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Data from: The effects of human-altered habitat spatial pattern on frugivory and seed dispersal: a global meta-analysis
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Data from: Citizen science and color pattern analysis indicate unreported Batesian mimicry between Neotropical snakes
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Data from: Genome-wide analysis reveals associations between climate and regional patterns of adaptive divergence and dispersal in American pikas
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Data from: Punctuated equilibria remains the dominant pattern of morphospecies origin in the fossil record: An analysis using the “persistence of ancestor” criterion
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Uncovering patterns of freshwater positive interactions using meta‐analysis: identifying the roles of common participants, invasive species and environmental context
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Fractal analysis of muscle activity patterns during locomotion: pitfalls and how to avoid them
<p>Despite the lack of consensus on how to perform fractal analysis of physiological time series, many studies rely on this technique. Here, we shed light on the potential pitfalls of using the Higuchi’s fractal dimension (HFD) and the Hurst exponent (H). We expose and suggest how to solve the drawbacks of such methods when applied to data from normal and perturbed locomotion by combining <em>in vivo</em> recordings and computational approaches.</p> <p>In this supplementary data set we made available: a) the metadata file “metadata.dat”; b) the baseline signals file “baseline_data.RData”; c) the R script “fractal_analysis.R” to calculate the H and HFD of the baseline data and produce the log-log plots. Explanatory comments are profusely present throughout the script and in the metadata file.</p>
Data from: Transcriptome analysis reveals nutrition‐ and age‐related patterns of gene expression in the fat body of pre‐overwintering bumble bee queens
<p>Many diapausing insects undergo a nutrient storage period prior to their entry into diapause. Bumble bee queens diapause as adults in the winter preceding their spring nest initiation period. Before diapause, they sequester glycogen and lipids, which they metabolize during the overwintering period. We used RNA sequencing to examine how age and nectar diet (specifically, the concentration of sucrose in nectar) impact gene expression in the pre-overwintering bumble bee queen fat body, the "liver-like" organ in insects with broad functions related to nutrient storage and metabolism. We found that diet on its own, and in combination with age, impacts the expression of genes involved in detoxification. Age was also a strong driver of gene expression, especially at earlier ages (up to 3 days). In addition to these molecular correlates of diet and age, we also found a putative molecular signature of diapause entry or preparation in adult queens in the oldest age group (12 days) fed the most sucrose-rich diet, based on comparisons between our data set and another transcriptome data set from bumble bee queens. This transcriptomic pattern suggests that preparation for (or entry into) diapause might be in part mediated by nutritional state in bumble bee queens. Collectively, these findings show that there are molecular processes in the fat body that are responsive to sucrose levels in the diet and/or associated with age-related maturational changes. A better understanding of these processes may shed light on important aspects of bumble bee biology, such as queen responses to nutritional and other forms of stress, and the factors that regulate their entrance into diapause.</p>
GPS locations for mechanistic home range analysis reveals drivers of space use patterns for a non-territorial passerine
<p>1. Home ranging is a near-ubiquitous phenomenon in the animal kingdom. Understanding the behavioural mechanisms that give rise to observed home range patterns is thus an important general question, and mechanistic home range analysis (MHRA) provides the tools to address it. However, such analysis has hitherto been restricted to scent-marking territorial animals, so its potential breadth of application has not been tested.</p> <p>2. Here, we apply MHRA to a population of long-tailed tits <em>Aegithalos caudatus </em>a non- territorial passerine, in the non-breeding season where there is no clear "central place" near which birds need to remain. The aim is to uncover the principal movement mechanisms underlying observed home range formation.</p> <p>3. Our foundational models consist of memory-mediated conspecific avoidance between flocks, combined with attraction to woodland. These are then modified to incorporate the effects of flock size and relatedness, to uncover the effect of these on the mechanisms of home range formation.</p> <p>4. We found that a simple model of spatial avoidance, together with attraction to the central parts of woodland areas, accurately captures long-tailed tit home range patterns. Refining these models further, we show that the magnitude of spatial avoidance by a flock is negatively correlated to both the relative size of the flock (compared to its neighbour) and the relatedness of the flock with its neighbour. </p> <p>5. Our study applies MHRA beyond the confines of scent-marking, territorial animals, so paves the way for much broader taxonomic application. These could potentially help uncover general properties underlying the emergence of animal space use patterns. This is also the first study to apply MHRA to questions of relatedness and flock size, thus broadening the potential possible applications of this suite of analytic techniques.<br> </p>
Data from: Landscape genetic analysis suggests stronger effects of past than current landscape structure on genetic patterns of Primula veris
<p>This dataset contains genetic and landscape data of 19 <i>Primula veris</i> populations in Muhu and Saaremaa islands in Estonia. Genetic samples were collected in 2015 and 2016. Landscape data was extracted from maps dated 2016 and 2017 for current data and 1930s for historical data. Data is divided to node- and link-based data. Node-based data contains genetic diversity data of the <i>P. veris</i> populations and landscape data in circular buffers surrounding the populations. Link-based data contains genetic differentiation between population pairs and landscape data in buffers surrounding a straight line between population pairs.</p>
Data from: Patterns of MHC-dependent mate selection in humans and non-human primates: a meta-analysis
Genes of the major histocompatibility complex (MHC) in vertebrates are integral for effective adaptive immune response and are associated with sexual selection. Evidence from a range of vertebrates supports MHC-based preference for diverse and dissimilar mating partners, but evidence from human mate choice studies has been disparate and controversial. Methodologies and sampling peculiarities specific to human studies make it difficult to know whether wide discrepancies in results among human populations are real or artefact. To better understand what processes may affect MHC-mediated mate choice across humans and nonhuman primates, we performed phylogenetically controlled meta-analyses using 58 effect sizes from 30 studies across seven primate species. Primates showed a general trend favouring more MHC-diverse mates, which was statistically significant for humans. In contrast, there was no tendency for MHC-dissimilar mate choice, and for humans, we observed effect sizes indicating selection of both MHC-dissimilar and MHC-similar mates. Focusing on MHC-similar effect sizes only, we found evidence that preference for MHC similarity was an artefact of population ethnic heterogeneity in observational studies but not among experimental studies with more control over sociocultural biases. This suggests that human assortative mating biases may be responsible for some patterns of MHC-based mate choice. Additionally, the overall effect sizes of primate MHC-based mating preferences are relatively weak (Fisher's Z correlation coefficient for dissimilarity Zr = 0.044, diversity Zr = 0.153), calling for careful sampling design in future studies. Overall, our results indicate that preference for more MHC-diverse mates is significant for humans and likely conserved across primates.
Data from: Cluster analysis successfully identifies clinically meaningful knee valgus moment patterns: frequency of early peaks reflects sex-specific ACL injury incidence
Background: Biomechanical studies of ACL injury risk factors frequently analyze only a fraction of the relevant data, and typically not in accordance with the injury mechanism. Extracting a peak value within a time series of relevance to ACL injuries is challenging due to differences in the relative timing and size of the peak value of interest. Aims/hypotheses: The aim was to cluster analyze the knee valgus moment time series curve shape in the early stance phase. We hypothesized that 1a) There would be few discrete curve shapes, 1b) there would be a shape reflecting an early peak of the knee valgus moment, 2a) youth athletes of both sexes would show similar frequencies of early peaks, 2b) adolescent girls would have greater early peak frequencies. Methods: N = 213 (39% boys) youth soccer and team handball athletes (phase 1) and N = 35 (45% boys) with 5 year follow-up data (phase 2) were recorded performing a change of direction task with 3D motion analysis and a force plate. The time series of the first 30% of stance phase were cluster analyzed based on Euclidean distances in two steps; shape-based main clusters with a transformed time series, and magnitude based sub-clusters with body weight normalized time series. Group differences (sex, phase) in curve shape frequencies, and shape-magnitude frequencies were tested with chi-squared tests. Results: Six discrete shape-clusters and 14 magnitude based sub-clusters were formed. Phase 1 boys had greater frequency of early peaks than phase 1 girls (38% vs 25% respectively, P < 0.001 for full test). Phase 2 girls had greater frequency of early peaks than phase 2 boys (42% vs 21% respectively, P < 0.001 for full test). Conclusions: Cluster analysis can reveal different patterns of curve shapes in biomechanical data, which likely reflect different movement strategies. The early peak shape is relatable to the ACL injury mechanism as the timing of its peak moment is consistent with the timing of injury. Greater frequency of early peaks demonstrated by Phase 2 girls is consistent with their higher risk of ACL injury in sports.
Data from: Large-scale parentage analysis reveals reproductive patterns and heritability of spawn timing in a hatchery population of steelhead (Oncorhynchus mykiss)
Understanding life history traits is an important first step in formulating effective conservation and management strategies. The use of artificial propagation and supplementation as such a strategy can have numerous effects on the supplemented natural populations and minimizing life history divergence is crucial in minimizing these effects. Here, we use single nucleotide polymorphism (SNP) genotypes for large-scale parentage analysis and pedigree reconstruction in a hatchery population of steelhead, the anadromous form of rainbow trout. Nearly complete sampling of the broodstock for several consecutive years in two hatchery programmes allowed inference about multiple aspects of life history. Reconstruction of cohort age distribution revealed a strong component of fish that spawn at 2 years of age, in contrast to programme goals and distinct from naturally spawning steelhead in the region, which raises a significant conservation concern. The first estimates of variance in family size for steelhead in this region can be used to calculate effective population size and probabilities of inbreeding, and estimation of iteroparity rate indicates that it is reduced by hatchery production. Finally, correlations between family members in the day of spawning revealed for the first time a strongly heritable component to this important life history trait in steelhead and demonstrated the potential for selection to alter life history traits rapidly in response to changes in environmental conditions. Taken together, these results demonstrate the extraordinary promise of SNP-based pedigree reconstruction for providing biological inference in high-fecundity organisms that is not easily achievable with traditional physical tags.
Data from: A meta-analysis reveals global patterns of sediment effects on marine biodiversity
Sediment disturbances are important threats affecting marine biodiversity, but the variety of biological responses have not yet been synthesized. Here, we collate all available information to compare the extent of impacts across different taxonomic groups, habitat types, and pathways of impact (light attenuation, suspended sediment and sedimentation). Global 1979-2017 Coral, fish, seagrass, sponge, macroalgae, ascidian, bryozoan, crustacean, echinoderm, mollusc, polychaeta We used meta-analyses to evaluate the effects of sediments across 842 observations found in 110 publications. We also evaluated some of the biological and methodological factors that could explain the variable effects observed in different studies. We found a significant negative effect of sediments on behavioural responses, reproduction and recruitment, organism's morphology, physiology, community abundance and diversity, and species interactions. In contrast, the overall effect on abundance of individual species was statistically non-significant and there was a strong positive effect on abundance for sponge and polychaete species. Many individual studies described physiological effects on coral reefs, but effects on diversity of soft-bottom and coral reef communities were particularly detrimental. Phototrophic species were generally more negatively impacted by sediments than heterotrophs, driven by strong physiological responses in crustose coralline algae and seagrass. Additionally, species with limited mobility were more vulnerable to sediment disturbances than highly mobile species. Sedimentation alone triggered more consistently negative effects on most biological responses than light depletion and suspended sediments. We found evidence for increased impacts on community diversity when more than one pathway of impact was present, indicating that these disturbances can disrupt whole ecosystems. Our meta-analysis for the first time provided strong quantitative support of negative effects of sediments on marine biodiversity. Taxonomic groups, habitat types, and life history characteristics were most influential in determining biological responses to sediment disturbances, highlighting the importance of an ecosystem-based approach when fully accounting for the impacts of sediment
Spatial point pattern analysis of traces (SPPAT): an approach for visualizing and quantifying site-selectivity patterns of drilling predators
<p>Site-selectivity analysis in drilling predation may provide useful behavioral information of a predator interacting with its prey. However, traditional approaches exclude some spatial information (i.e., oversimplified trace position) and are dependent on the scale of analysis (e.g., arbitrary grid system used to divide the prey skeleton into sectors). Here we introduce the spatial point pattern analysis of traces (<i>SPPAT</i>), an approach for visualizing and quantifying the distribution of traces on shelled invertebrate prey, which includes improved collection of spatial information inherent to drillhole location (morphometric-based estimation), improved visualization of spatial trends (Kernel density and hotspot mapping), and distance-based statistics for hypothesis testing (<i>K</i>-, <i>L</i>-, and pair correlation functions). We illustrate the <i>SPPAT</i> approach through case studies of fossil samples, modern beach-collected samples, and laboratory feeding trials of naticid gastropod predation on bivalve prey. Overall results show that Kernel density and hotspot maps enable visualization of subtle variations in regions of the shell with higher density of predation traces, which can be combined with the maximum clustering distance metric to generate hypotheses on predatory behavior and anti-predatory responses of prey across time and geographic space. Distance-based statistics also capture the major features in the distribution of traces across the prey skeleton, including aggregated and segregated clusters, likely associated with different combinations of two modes of drilling predation, edge- and wall-drilling. The <i>SPPAT </i>approach is transferrable to other paleoecologic and taphonomic data such as encrustation and bioerosion, allowing for standardized investigation of a wide range of biotic interactions.</p>
Data from: Spatiotemporal patterns of duck nest density and predation risk: a multi-scale analysis of 18 years and more than 10 000 nests
Many avian species are behaviorally-plastic in selecting nest sites, and may shift to new locations or habitats following an unsuccessful breeding attempt. If there is predictable spatial variation in predation risk, the process of many individuals using prior experience to adaptively change nest sites may scale up to create shifting patterns of nest density at a population level. We used 18 years of waterfowl nesting data to assess whether there were areas of consistently high or low predation risk, and whether low-risk areas increased, and high-risk areas decreased in nest density the following year. We created kernel density maps of successful and unsuccessful nests in consecutive years and found no correlation in predation risk and no evidence for adaptive shifts, although nest density was correlated between years. We also examined between-year correlations in nest density and nest success at three smaller spatial scales: individual nesting fields (10–28 ha), 16-ha grid cells and 4-ha grid cells. Here, results were similar across all scales: we found no evidence for year-to-year correlation in nest success but found strong evidence that nest density was correlated between years, and areas of high nest success increased in nest density the following year. Prior research in this system has demonstrated that areas of high nest density have higher nest success, and taken together, our results suggest that ducks may adaptively select nest sites based on the local density of conspecifics, rather than the physical location of last year's nest. In unpredictable environments, current cues, such as the presence of active conspecific nests, may be especially useful in selecting nest sites. The cues birds use to select breeding locations and successfully avoid predators deserve continued attention, especially in systems of conservation concern.
ScienceDex guides
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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.