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149 results for “Variability, spatial”
Data from: Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks
Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes.
Data from: Patterns of diversity and spatial variability of β-defensin innate immune genes in a declining wild population of tree swallows
Assessing the genetic variation and distribution of immune genes across heterogeneous environmental conditions in wild species is essential to further our understanding of the role of pathogen pressure and potential resistance or prevalence in hosts. Researchers have recently investigated β-defensin genes in the wild, because their variability suggests that they may play an important role in innate host defense. This study investigated the variation occurring at 6 innate immune genes of the β-defensin family in a declining population of tree swallows (Tachycineta bicolor) in southern Québec, Canada (N = 160). We found that all 6 genes showed synonymous and nonsynonymous single nucleotide polymorphisms (SNPs) within the exon coding for the mature peptide. These results indicated that this group of genes was diverse in tree swallows. Our results suggested a potential interaction of this group of genes with fluctuating pathogen diversity, however, we found no sign of positive or negative selection. We assessed whether or not the distribution of genetic diversity of β-defensin genes in our study population differed between 2 regions that strongly differ in their level of agricultural intensification. Adults are highly philopatric to their breeding sites and their immunological responses differ between these 2 regions. However, we found little evidence that the level and distribution of genetic variability differed between these heterogeneous environmental conditions. Further studies should aim to assess the link between genetic diversity of β-defensin genes and fitness-related traits in wild populations.
Data from: Spatial variability in plant predation determines the strength of stochastic community assembly
High diversity is often poorly explained by trait-based deterministic models, in part because stochastic processes also influence community assembly. Testing how deterministic and stochastic processes combine to regulate diversity, however, has been limited by the spatial complexity of these interactions. Here, we demonstrate how spatial variability in small-mammal predation on plants, mostly by granivory, results in fine-scale switching between deterministically and stochastically regulated plant community assembly in an otherwise environmentally homogeneous tallgrass prairie. We initiated assembly with the uniform application of a 24-species mixture of prairie grasses and forbs, thereby setting the maximum level of diversity (γ-diversity). In field edges with higher densities of small mammals, traits reducing seed palatability deterministically produced homogeneous subsets of less palatable plant species within the first few months after planting (low α and β diversity). As small-mammal densities decreased in more open areas, assembly unfolded stochastically on the basis of which planted species happened to land at a given location (high α and β diversity). We used randomization models to validate that this higher β diversity was explained by true differences in community structure among plots rather than by the hidden effects of increasing α diversity. The net effect at the site level was a spatially structured array of prairie species, including a positive relationship between diversity and environmental suitability relating to reduced predator intensity.
Data in support to the paper: Comparison of Soil Water Content from SCATSAR-SWI and Cosmic Ray Neutron Sensing at four agricultural sites in Northern Italy: insights from spatial variability and representativeness by Emamalizadeh et al. (2024)
<p>The study was conducted within the 21GRD08 SoMMet project. The SoMMet project has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States (funder name European Partnership on Metrology; funder ID 10.13039/100019599; grant no. 21GRD08 SoMMet).</p>
Dataset for Can we predict kick force based solely on spatial-temporal variables? Applying long short-term memory model for predicting force values of turning and side kick of taekwon-do athletes
<p>This data set is created for a purpose of publication "<span>Can we predict kick force based solely on spatial-temporal variables? Applying long short-term memory model for predicting force values of turning and side kick of taekwon-do athletes". It contains of dataset of kicks and lstm models for predictions a force of kicks upon IMU data. Detailed description of file names are in readme file. Folders are divided into specific kicks - turning or side kick in sport or traditional versions.</span></p>
Learning tasks and result data for the 2024 GECCO short paper Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning
<p>Learning tasks and result data for the 2024 GECCO short paper Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning by David Pätzel, Richard Nordsieck and Jörg Hähner.</p>
Spatial variability and driving factors of ecosystem services balance at watershed scale in the Lancang River Valley, Southwest China
<p>Revealing the spatio-temporal change of the supply, demand and balance of ecosystem services (ES) associated with human activities and land use changes is of great significance for watershed ecosystem management. Taking the Lancang River Valley as a case, we explicitly studied the ES spatial characteristics using the land use/land cover (LULC) matrix model, Optimized Hot Spot Analysis and landscape pattern analysis. Further, we screened out the dominant explanatory variables which had significant influence on ES supply, demand and balance by means of Geographical Weighted Regression (GWR) method at pixel scale. The results showed that the ES demand intensity varied little throughout the watershed while the downstream ES supply capacity and balance value were greater than upstream. Meanwhile, the hotspots of ES supply and demand were mainly distributed in the south part but coldspots in the north part. Human activity factors integrating landscape pattern variables were verified to have negative impact on ES balance in general. Among them, the Largest Patch Index (LPI) had a negative influence of majority pixels while GDP, cultivated land ratio and Area Weighted Average Patch Fractal Dimension (AWAPFD) had positive effects on a few pixels. This study will provide scientific support for regional ecosystem service trade-off and regulation at multiple scales.</p>
Learning tasks and result data for the 2024 IWERL@GECCO paper A Closer Look at Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning
<p>Learning tasks and result data for the paper Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning by David Pätzel, Richard Nordsieck and Jörg Hähner, presented at the International Workshop on Evolutionary Rule-based Machine Learning taking place as part of GECCO 2024.</p>
Data Sets for: Trace elements in aerosol from Northwest Pacific marginal sea, Indian Ocean and South Pacific to Antarctica: Spatial variability and source identification
<p>This dataset includes the concentrations of trace elements in aerosols, along with location and time information, collected during a cruise from November 2021 to April 2022. The cruise covered the Pacific, the Indian Ocean, the Southern Ocean.</p>
Systematic benchmarking of computational methods to identify spatially variable genes: Part 1
<div> <div> <div> <p>Spatially resolved transcriptomics offers unprecedented insight by enabling the profiling of gene expression within the intact spatial context of cells, effectively adding a new and essential dimension to data interpretation. To efficiently detect spatial structure of interest, an essential step in analyzing such data involves identifying spatially variable genes. Despite researchers having developed several computational methods to accomplish this task, the lack of a comprehensive benchmark evaluating their performance remains a considerable gap in the field. Here, we present a systematic evaluation of 14 methods using 60 simulated datasets generated by four different simulation strategies, 12 real-world transcriptomics, and three spatial ATAC-seq datasets. We find that spatialDE2 consistently outperforms the other benchmarked methods, and Moran’s I achieves competitive performance in different experimental settings. Moreover, our results reveal that more specialized algorithms are needed to identify spatially variable peaks. </p> <p> </p> </div> </div> </div>
The Dataset of the paper "Seasonal and spatial variability and mechanisms of suspended sediment concentration in the Yellow River mouth and adjacent waters"
<div> <p>The data for "Seasonal and spatial variability and mechanisms of suspended sediment concentration in the Yellow River mouth and adjacent waters". The file names correspond to the figures in the paper.</p> </div>
Data from: Non-equilibrium conditions explain spatial variability in genetic structuring of little penguin (Eudyptula minor)
Factors responsible for spatial structuring of population genetic variation are varied, and in many instances there may be no obvious explanations for genetic structuring observed, or those invoked may reflect spurious correlations. A study of little penguins (Eudyptula minor) in southeast Australia documented low spatial structuring of genetic variation with the exception of colonies at the western limit of sampling, and this distinction was attributed to an intervening oceanographic feature (Bonney Upwelling), differences in breeding phenology, or sea level change. Here, we conducted sampling across the entire Australian range, employing additional markers (12 microsatellites and mitochondrial DNA, 697 individuals, 17 colonies). The zone of elevated genetic structuring previously observed actually represents the eastern half of a genetic cline, within which structuring exists over much shorter spatial scales than elsewhere. Colonies separated by as little as 27 km in the zone are genetically distinguishable, while outside the zone, homogeneity cannot be rejected at scales of up to 1400 km. Given a lack of additional physical or environmental barriers to gene flow, the zone of elevated genetic structuring may reflect secondary contact of lineages (with or without selection against interbreeding), or recent colonization and expansion from this region. This study highlights the importance of sampling scale to reveal the cause of genetic structuring.
Data from: The ghost of introduction past: spatial and temporal variability in the genetic diversity of invasive smallmouth bass
Understanding the demographic history of introduced populations is essential for unravelling their invasive potential and adaptability to a novel environment. To this end, levels of genetic diversity within the native and invasive range of a species are often compared. Most studies, however, focus solely on contemporary samples, relying heavily on the premise that the historic population structure within the native range has been maintained over time. Here, we assess this assumption by conducting a three-way comparison of the genetic diversity of native (historic and contemporary) and invasive (contemporary) smallmouth bass (Micropterus dolomieu) populations. Analyses of a total of 572 M. dolomieu samples, representing the contemporary invasive South African range, contemporary and historical native USA range (dating back to the 1930s when these fish were first introduced into South Africa), revealed that the historical native range had higher genetic diversity levels when compared to both contemporary native and invasive ranges. These results suggest that both contemporary populations experienced a recent genetic bottleneck. Furthermore, the invasive range displayed significant population structure, whereas both historical and contemporary native USA populations revealed higher levels of admixture. Comparison of contemporary and historical samples showed both a historic introduction of M. dolomieu, as well as a more recent introduction, thereby demonstrating that undocumented introductions of this species have occurred. Although multiple introductions might have contributed to the high levels of genetic diversity in the invaded range, we discuss alternative factors that may have been responsible for the elevated levels of genetic diversity and highlight the importance of incorporating historic specimens into demographic analyses.
Spatial and temporal drivers of in situ fluorescence quantum yield variability in the Southern Ocean
<p>The datasets in this repository are part of the manuscript entitled "Spatial and temporal drivers of in situ fluorescence quantum yield variability in the Southern Ocean".</p>
Video related to the study "Spatial variability of Saharan dust deposition revealed through a citizen science campaign"
<p>This video is related to the manuscript "Spatial variability of Saharan dust deposition revealed through a citizen science campaign", by Dumont et al., submitted in December 2022 to the journal "Earth System Science Data".</p> <p>It illustrates the timeline of dust deposition, simulated by the atmospheric transport model MOCAGE.</p> <p> </p>
Dataset related to the study "Spatial variability of Saharan dust deposition revealed through a citizen science campaign"
<p>This dataset contains the data and the measurements related to the manuscript "Spatial variability of Saharan dust deposition revealed through a citizen science campaign", by Dumont et al., submitted in December 2022 to the journal "Earth System Science Data".</p> <p> </p>
Small scale spatial variability in diffusive erosion and deposition simulation data
<p>Small scale spatial variability in diffusive erosion and deposition simulation data</p>
Data from: Spatial variability in a plant-pollinator community across a continuous habitat: high heterogeneity in the face of apparent uniformity
Open the record for dataset details and reuse information.
Data from: Temporal variability in the environmental and geographic predictors of spatial-recruitment in nearshore rockfishes
Open the record for dataset details and reuse information.
Data from: The ghost of introduction past: spatial and temporal variability in the genetic diversity of invasive smallmouth bass
Open the record for dataset details and reuse information.
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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.