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411 results for “spatial variation”
Spatial variation in current and historical management of Arabica coffee across forests in its indigenous distribution
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Data from: Spatial and seasonal variation in thermal sensitivity within North American bird species
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Spatial variation in the evolutionary potential and constraints of basal metabolic rate and body mass in a wild bird
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Data from: Genomics-informed conservation units reveal spatial variation in climate vulnerability in a migratory bird
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Data from: A species' response to spatial climatic variation does not predict its response to climate change
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Linking spatial variations in life-history traits to environmental conditions across American black bear populations
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Spatial Variation of Soil Carbon, Nitrogen and Phosphorus in the Luquillo Experimental Forest (LEF) (LEF_SOIL_CNP)
Hongqing Wang, a Ph.D graduate student of SUNY-ESF, with the help of many others, took soil samples in 119 locations over the entire Luquillo Experimental Forest (LEF) during the summer of 1998 and 1999. Soil organic carbon, total nitrogen and acid-extractable phosphorus were measured in the laboratory of SUNY-ESF; soil moisture and bulk density were measured at the laboratory of the El Verde Station of UPR. The geodetic coordinates (Lat., Lon.) and elevation of each sampling location were determined using a Global Positioning System (GPS Pathfinder Basic Receivers, Trimble Navigation Ltd.) in the field. Meanwhile, slope angle, aspect and topographic features (Ridge, slope I (<35 deg.), slope II (>=35 deg.), valleys) were also measured and observed in the field. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Data from: Spatial scale, neighbouring plants and variation in plant volatiles interactively determine the strength of host-parasitoid relationships
Species-specific responses to the environment can moderate the strength of interactions between plants, herbivores and parasitoids. However, the ways in which characteristics of plants, such as genotypic variation in herbivore induced volatiles (HIPVs) that attract parasitoids, affect trophic interactions in different contexts of plant patch size and plant neighbourhood is not well understood. We conducted a factorial field experiment with white cabbage (<i>Brassica oleracea</i>) accessions that differ in the attractiveness of their HIPVs for parasitoids, in the context of different patch sizes and presence or absence of surrounding <i>Brassica nigra</i> plants. Parasitism rates of experimentally introduced <i>Pieris brassicae</i> caterpillars and the presence of naturally occurring <i>Pieris</i> spp. caterpillars in the plots were assessed throughout the growing season. The abundance of <i>Pieris</i> caterpillars was neither affected by cabbage accession nor plot size. Later in the season, when <i>B. nigra</i> plants had senesced, fewer caterpillars were found on cabbage plants in plots with a <i>B. nigra</i> border. Parasitism rates fluctuated over the season, and were not affected by plot size. However, the <i>B. nigra</i> border negatively affected parasitism rates on the accession that is less attractive to the parasitoid <i>Cotesia glomerata</i>, but not on the more attractive accession. Our results show that plant variation in HIPVs can differentially influence herbivores and parasitoids depending on characteristics of the surrounding vegetation context. These findings underscore the importance of considering the interaction between focal plant traits and neighbourhood context to reliably predict trophic cascades.
The degree of spatial variation relative to temporal variation influences evolution of dispersal
In the face of ongoing global climate an land use change, organisms have multiple possibilities to cope with the modification of their environment. The two main possibilities are to either adapt locall or disperse to a more suitable habitat. The evolution of both local adaptation and dispersal interacts and can be influenced by the spatial and temporal variation (of e.g. temperature or precipitation). In an individual based model (IBM), we explore evolution of phenotypes in landscapes with varying degree of spatial relative to global temporal variation in order to examine it's influence on the evolution of dispersal, niche optimum and niche width. The relationship between temporal and spatial variation did neither influence the evolution of local adaptation in the niche optimum nor of niche widths. Dispersal probability is highly influenced by the spatio-temporal relationship: with increasing spatial variation, dispersal probability decreases. Additionally, the shape of the distribution of the trait values over patch attributes switches from hump- to U-shaped. At low spatial variance more individuals emigrate from average habitats, at high spatial variance more from extreme habitats. The comparatively high dispersal probability in extreme patches of landscapes with a high spatial variation can be explained by evolutionary succession of two kinds of adaptive response. Early in the simulations, extreme patches in landscapes with a high spatial variability act as sink habitats, where population persistence depends on highly dispersive individuals with a wide niche. With ongoing evolution, local adaptation of the remaining individuals takes over, but simultaneously a possible bet-hedging strategy promotes higher dispersal probabilities in those habitats. Here, in generations that experience extreme shifts from the temporal mean of the patch attribute, the expected fitness becomes higher for dispersing individuals than for philopatric individuals. This means under certain circumstances, both local adaptation and high dispersal probability can be selected for.
Detecting phylogenetic signal and adaptation in papionin cranial shape by decomposing variation at different spatial scales
<p>Phylogenetic reconstruction based on morphometric data is hampered by homoplasies. For example, many similarities in cranial form between primate taxa more strongly reflect ecological similarities rather than phylogenetic relatedness. However, the way in which the different cranial bones constitute cranial form is, if at all, of less functional relevance and thus largely hidden from selection. We propose that these "constructional details" are better indicators of phylogenetic history than any large-scale shape feature or raw form variable. Within a geometric morphometric context, we show how to analyze the relative extent of bones independently of differences in overall shape. We also show how to decompose total shape variation into small-scale and large-scale shape variation. We apply both methods to the midsagittal cranial morphology of papionin monkeys, which are well known for the discrepancy between morphological similarities and phylogenetic relationships. We study phylogenetic signal and functional adaptation using a molecular phylogeny and contextual data on feeding ecology and locomotor behavior. As expected, total cranial shape, bone outline shape, and large-scale shape features were only weakly associated with phylogenetic distance. But the relative bone contributions and small-scale shape features were both highly correlated with phylogenetic distances. By contrast, the association with ecological and behavioral variables was strongest for the outline shape and large-scale shape features. Studies of morphological adaptation and phylogenetic history thus profit from a decomposition of shape variation into different spatial scales.</p>
Data from: Repeatable patterns of small-scale spatial variation in intertidal mussel beds and their implications for responses to climate change
The interaction of ocean conditions and weather with small-scale physical features of a habitat can have profound effects on the experiences of individual organisms. On topographically complex shorelines, and particularly within dense aggregations of organisms such as mussel beds, a mosaic of environmental conditions can develop, and the resulting variation in conditions within the aggregation could drastically alter the performance of neighboring individuals. Using a suite of sensors mounted to individual Mytilus californianus mussels over two summer field deployments, we have characterized the temperature variation and valve gaping behavior differences found at two spatial scales: within a group separated by centimeters, and between groups of mussels located at the upper and lower extents of the natural mussel zone separated by meters. While temperature conditions near the lower edge of the mussel bed were generally more benign, temperature extremes were similar at both heights in the bed, and variation in body temperature among neighbors increased as the daily mean temperature increased. These patterns were similar across years despite a 3.8°C difference in mean air and seawater temperatures between years. Gaping behavior was also highly variable among individuals, though that variability diminished at the high end of the mussel bed where the total time mussels spent submerged was much more constrained. These data indicate that an individual mussel's physiological status and past history can be drastically different than those of its nearby neighbors, complicating our ability to characterize representative conditions within a habitat. These observations also provide for the possibility that the impacts of future climate change will be highly specific to certain individuals based on their relative exposure or protection within the mosaic. To address such possibilities, future work must examine the correlation between genotypic and physiological traits that determine performance and individuals' unique experiences in their disparate micro-environments.
Data from: Species-specific variation in germination rates contributes to spatial coexistence more than adult plant water use in four closely-related annual flowering plants
1. Spatial partitioning is a classic hypothesis to explain plant species coexistence, but evidence linking local environmental variation to spatial sorting, demography, and species' traits is sparse. If co-occurring species' performance is optimized differently along environmental gradients because of trait variation, then spatial variation might facilitate coexistence. 2. We used a system of four naturally co-occurring species of Clarkia (Onagraceae) to ask if distribution patchiness corresponds to variation in two environmental variables that contribute to hydrological variation. We then reciprocally sowed Clarkia into each patch type and measured demographic rates in the absence of congeneric competition. Species sorted in patches along one or both gradients, and in three of the four species, germination rate in the "home" patch was higher than all other patches. 3. Spatially variable germination resulted in the same three species exhibiting the highest population growth rates in their home patches. 4. Species' trait values related to plant water use, as well as indicators of water stress in home patches, differed among species and corresponded to home patch attributes. However, post-germination survival did not vary among species or between patch types, and fecundity did not vary spatially. 5. Synthesis Our research demonstrates the likelihood that within-community spatial heterogeneity affects plant species coexistence, and presents novel evidence that differential performance in space is explained by what happens in the germination stage. Despite the seemingly obvious link between adult plant water-use and variation in the environment, our results distinguish the germination stage as important for spatially variable population performance.
Spatial and temporal heterogeneity in pollinator communities maintains within-species floral odour variation
<p>Flowering plants emit complex bouquets of volatile organic compounds (VOCs) to mediate interactions with their pollinators. These bouquets are undoubtedly influenced by pollinator-mediated selection, particularly in deceptively-pollinated species that rely on chemical mimicry. However, many uncertainties remain regarding how spatially and temporally heterogeneous pollinators affect the diversity and distribution of floral odour variation. Here, we characterized and compared the floral odours of ten populations of deceptively-pollinated <em>Arum maculatum</em> (Araceae), and inter-annual and decadal variation in pollinator attraction within these populations. Additionally, we transplanted individuals from all sampled populations to two common garden sites dominated by different pollinator species (<em>Psychoda phalaenoides</em> or <em>Psycha grisescens</em>), and compared pollinator attraction rates to investigate whether populations maintained odour blends adapted to a specific pollinator. We identified high within- and among-population variation in a common blend of VOCs found across the range of <em>A. maculatum</em>. We also observed shifts in pollinator community composition within several populations over 1-2 years, as well as over the past decade. Common garden experiments further revealed that transplanted inflorescences generally attracted the dominant local pollinator species in both transplant sites. However, one population (Forêt du Gâvre, France) appears to exclusively attract <em>P. grisescens</em>, even when transplanted to a <em>P. phalaenoides</em>-dominated site. Together, our results suggest that maintaining diverse floral odour bouquets within populations may be advantageous when pollinator communities vary over short timescales. We propose that temporally-replicated ecological data are one potential key to understanding variation in complex traits such as floral odour, and in some cases may reveal resiliency to shifting pollinator communities.</p>
Data from: Spatial variation of the rain-snow temperature threshold across the Northern Hemisphere
We present the first continuous map of rain-snow air temperature thresholds over the Northern Hemisphere land surface, underlining the spatial variability of precipitation phase partitioning. Land surface models typically discriminate between rain and snow using a simple, spatially uniform air temperature threshold, but observations indicate the threshold is not static. Our analysis of a 29-year observational dataset (n = 17.8 million) shows the threshold varies significantly, averaging 1.0°C and ranging from -0.4°C to 2.4°C for 95% of Northern Hemisphere stations, with continental climates exhibiting the warmest thresholds and maritime the coolest. Relative humidity exerts the strongest control on phase partitioning, while surface pressure plays a secondary role. Simulations indicate the selection of a rain-snow threshold introduces significant uncertainty to snowfall frequency and that including relative humidity as a predictor variable provides the greatest improvement to precipitation phase prediction between 0.6°C and 3.4°C, the interval where phase partitioning is most uncertain.
Urban area age and coefficient of variation of spatial area extent
<p>The dataset contains an proxy for the age of urban area and the coefficient of variation of its spatial extent as proxy for spatial dynamics. Both variables are studied as key to conceptualize the process of urbanization by means of clusters of local spatial autocorrelation. The analysis is based on the HYDE 3.1 database, cf. Klein Goldewijk et al. (2010), Klein Goldewijk et al. (2011).</p>
Spatial variation and inconsistency between estimates of onset of muscle activation from EMG and ultrasound
<p>Study abstract: Delayed onset of muscle activation is a descriptor of impaired motor control. Activation<br> onset can be estimated from electromyography (EMG)-registered muscle excitation and<br> from ultrasound-registered muscle motion, which enables non-invasive measurements in<br> deep muscles. However, in voluntary activation, EMG- and ultrasound-detected activation<br> onsets may not correspond. To evaluate this, ten healthy men performed isometric elbow<br> flexion at 20% to 70% of their maximal force. Utilising a multi-channel electrode<br> transparent to ultrasound, EMG and M(otion)-mode ultrasound were recorded<br> simultaneously over the biceps brachii muscle. The time intervals between automated and<br> visually estimated activation onsets were correlated with the regional variation of EMG<br> and muscle motion onset, contraction level and speed. Automated and visual onsets<br> indicated variable time intervals between EMG- and motion onset, median (interquartile<br> range) 96 (121) ms and 48 (72) ms, respectively. In 17% of trials (computed analysis) or<br> 23% (visual analysis), motion onset was detected before local EMG onset. Multi-channel<br> EMG and M-mode ultrasound revealed regional differences in activation onset, which<br> decreased with higher contraction speed (Spearman ρ≥0.45, P<0.001). In voluntary<br> activation the heterogeneous motor unit recruitment together with immediate motion<br> transmission may explain the high variation of the time intervals between local EMG- and<br> ultrasound-detected activation onset.</p> <p>Data description:</p> <p><strong>EMG data:</strong> folder includes the EMG, torque and synchronization signal data as .otb files. The respective program can be downloaded without costs from http://www.otbioelettronica.it/index.php?lang=en. Data consist of two series (Misome2 and Misome3) of isometric trials at different force levels. The first three digits refer to the subject number.</p> <p><strong>M-mode ultrasound data</strong>: folder includes the M-mode clips of all recorded trials in .tvd format. The respective program can be downloaded for free at http://www.telemedultrasound.com/download/software-downloads/?lang=en. In addition, images of activation onset in DICOM format are provided. The data are sorted for subjects and series (Misome2 and Misome3). The following explanation refers to the filenames of the DICOM images. Usually, the M-mode trace started at the left side synchronously with the synch signal. In this case the rightmost frame of the trace is missing to indicate that the left edge represents the start of the trace. If the file name includes “ons50”, the frame includes the 50. frame = the rightmost frame, still starting with the synch signal. If the filename includes on100, the rightmost frame is the 100. frame and the duration of 50 frames must be added to the visible onset time. Filenames that include “basel” refer to frames that represent a proper delineation of the baseline.</p> <p><strong>Excel data sheet</strong>: Data sheet that includes the computed and visual EMG, M-mode ultrasound and torque onsets, the rate of torque development and the differences between the different types of onsets. The column headers explain the data type, most comprehensively in the first computed data sheet. The colors facilitate the orientation with blue columns referring to torque onsets and green columns referring to ultrasound onsets. The violet EMG channels are those in vicinity to the ultrasound beam. In the second version of each sheet the 5% slowest trials are separated.</p>
Spatial source contribution and interannual variation in deposition of dust aerosols over the Chinese Loess Plateau (Haugvaldstad et al 2024)
<h2>Spatial source contribution and interannual variation in deposition of dust aerosols over the Chinese Loess Plateau</h2> <h4>Description:</h4> <p>The data.zip file contains processed FLEXPART/FLEXDUST and ERA5 data. ERA5 is used for meteorological analysis. FLEXDUST is the dust emission inventory used for calculating the source contribution. Combined source contribution is separated for each receptor site. The "clay" suffix in the file name refers the fine dust size-bin, the "silt" suffix refers to the super-coarse size-bin. For more information look at the published manuscript. The MERRA2.zip contain the data used in the FLEXPART MERRA2 intercomparison.</p> <p>The complete 3hourly FLEXPART source contribution and Emissions sensitivity are available from the Norwegian research data archive (DOI: <a href="https://doi.org/10.11582/2023.00135">10.11582/2023.00135</a>). The simulated FLEXDUST 3 hourly dust emission are also available from the Norwegian research data archive (DOI: <a href="https://doi.org/10.11582/2023.00134">10.11582/2023.00134</a>)</p> <h4>Data Format:</h4> <p>NetCDF4, CSV</p> <h4>Usage Notes:</h4> <p>The content of the zip file is used to generate the figures shown in Haugvaldstad et al 2023. To processes and recreate the figures in the manuscript there is a provided docker image that can be pulled with the following command: <em>docker pull ovewh/thesisdocker:build1.1.8</em>. More info <a href="https://hub.docker.com/r/ovewh/thesisdocker">here. </a></p> <p>The following GitHub repositories are used to analyse and plot the data, if the docker image is used codes should be downloaded automatically. </p> <ul> <li>Snakemake workflow: <a href="https://github.com/MasterOnDust/AGU_JGR_CLP_SOURCE_WORKFLOW/tree/AGU-Haugvaldstad-et-al-2023">https://github.com/MasterOnDust/AGU_JGR_CLP_SOURCE_WORKFLOW/tree/AGU-Haugvaldstad-et-al-2023</a></li> <li>Python library with plotting functionality and analysis utilities: <a href="https://github.com/MasterOnDust/Thesis_toolbox/tree/AGU-Haugvaldstad-et-al-2023">https://github.com/MasterOnDust/Thesis_toolbox/tree/AGU-Haugvaldstad-et-al-2023</a></li> <li>Python library for trajectory analysis: <a href="https://github.com/MasterOnDust/flexpart_cluster/tree/AGU-Haugvaldstad-et-al-2023">https://github.com/MasterOnDust/flexpart_cluster/tree/AGU-Haugvaldstad-et-al-2023</a></li> <li>Python library for reading and post processing for FLEXPART and FLEXDUST raw output: <a href="https://github.com/MasterOnDust/DUST/tree/AGU-Haugvaldstad-et-al-2023">https://github.com/MasterOnDust/DUST/tree/AGU-Haugvaldstad-et-al-2023</a></li> </ul>
Data from: Distances and their visualization in studies of spatial-temporal genetic variation using single nucleotide polymorphisms (SNPs)
<p>Distance measures are widely used for examining genetic structure in datasets that comprise many individuals scored for a very large number of attributes. Genotype datasets composed of single nucleotide polymorphisms (SNPs) typically contain bi-allelic scores for tens of thousands if not hundreds of thousands of loci.</p> <p>We examine the application of distance measures to SNP genotypes and sequence tag presence-absences (SilicoDArT) and use real datasets and simulated data to illustrate pitfalls in the application of genetic distances and their visualization.</p> <p>The datasets used to illustrate points in the associated review are provided here together with the R script used to analyse the data. Data are either simulated internal to this script or are SNP data generated as part of other studies and included as compressed binary files readily accessable by reading into R using R base function readRDS(). Refer to the analysis script for examples.</p>
Spatial variation in avian bill size is associated with temperature extremes in a major radiation of Australian passerines
<p>Morphology is integral to body temperature regulation. Recent advances in understanding of thermal physiology suggest a role of the avian bill in thermoregulation. To explore the adaptive significance of bill size for thermoregulation we characterized relationships between bill size and climate extremes. Most previous studies have focussed on climate means, ignoring extremes, and do not reflect thermoregulatory costs experienced over shorter time scales. Using 79 species (9,847 museum specimens), we explore how bill size variation is associated with temperature extremes in a large and diverse radiation of Australasian birds, Meliphagides. Overall, across the continent, bill size variation was associated with both climate extremes and means and was most strongly associated with winter temperatures; associations at the level of climate zones differed from continent-wide associations, were complex and non-linear, yet consistent with physiology and a thermoregulatory role for avian bills. We provide strong evidence that climate extremes have contributed to the evolution of bill morphology in relation to thermoregulation and demonstrate the importance of including extremes to understand fine-scale trait variation across space. Increasing frequency and intensity of climate extremes, a signature of climate change, may lead to changes in bill size, but this is yet to be tested.</p>
Temporal and spatial variation of zooplankton in relation to environmental variables in the upper Santos estuary, São Paulo, Brazil
<p><span>Zooplankton samples were collected through oblique trawls with a 200 µm net with a flow meter during low tide, at 4 sampling sites with different degrees of salinity in the upper Santos estuary, in 28 campaigns carried out between 2014 and 2023, to analyze the spatial and temporal variations in the structure and abundance of zooplankton in relation to environmental variables using data from a long-term monitoring, in this way, contributing to the update of knowledge about the zooplankton community of the Santos estuary. </span></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.