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261 results for “spatial effects”
Data and script for "On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"
<p>Data and R script necessary to replicate the results of Riva et al. 2024 ("On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"; minor revisions, Biological Conservation).</p>
Effect of spatial input data quality on SWAT modelling in the Porijõgi catchment
<p>The Porijõgi Catchment near Tartu, Estonia is the study area for this research. Four model setups were created using global/regional level data (HWSD soil, CORINE), and local high-resolution spatial data including the new Estonian high-resolution EstSoil-EH soil dataset and the Estonian Topographic Database (ETAK). The study employed statistical criteria to assess SWAT model performance for monthly simulated stream flows from 2007 to 2019.</p> <p>Data deposit in preparation for article:</p> <p>Effect of spatial input data quality on the uncertainty of the<br> SWAT model, submitted 2022</p> <p>Alexander Kmoch, Desalew Meseret Moges, Mahdiyeh Sepehrar, Balaji Narasimhan and Evelyn<br> Uuemaa</p> <p>contact: alexander.kmoch@ut.ee</p>
Effects of audio-motor training on spatial representations in long-term late blindness
<p>Datasets for behavioural data:</p> <p>-<em>Auditory horizontal localization task</em></p> <p>- <em>Auditory vertical localization task</em></p> <p>- <em>Position matching task</em></p> <p>- <em>Proprioceptive midline task</em></p> <p>Dataset for EEG data:</p> <p>- Spatial bisection task: mean ERP amplitude for 50-90ms timew window for each trial, separately for condition, session and roi</p> <p> </p>
Data from publication: Castillioni, K., & Isbell, F. (2023). Early positive spatial selection effects of beta-diversity on ecosystem functioning. Landscape Ecology, 1-15.
Data from publication: Castillioni, K., & Isbell, F. (2023). Early positive spatial selection effects of beta-diversity on ecosystem functioning. Landscape Ecology, 1-15. Spatial beta-diversity may increase landscape productivity if there are positive spatial selection effects. Alternatively, dominant species in mixtures might not be the most productive species in monoculture leading to negative or neutral spatial selection effects. However, these hypotheses remain untested experimentally. Seedling survival can determine species establishment, influencing productivity later. To address this knowledge gap, we experimentally tested whether transplanted seedlings of dominant species optimally sort among habitat types (grassland dominated by Andropogon gerardii, savanna by Quercus macrocarpa, deciduous forest by Acer rubrum, coniferous forest by Pinus strobus, bog by Larix laricina), creating positive effects of landscape diversity on seedling survival and net biodiversity effects at Cedar Creek Ecosystem Science Reserve (CCESR) in Minnesota, USA. The study is named BetaDIV and consists of 100 plots (20 plots per habitat × 5 habitats). Each of the five habitats includes two true replicate monocultures for each of the five species and two true replicates for each of the five possible mixture compositions of four species (leaving each one out in turn to eventually explore the effect of species identity). Each plot is 1.5 by 1.5 m, with 12 seedlings planted 0.5 m apart in a 4 × 4 square grid, except in the plot corners. In the early June 2022, we tagged and planted all seedlings (i.e., bareroot seedlings for trees and plugs for the grass A. gerardii). Two weeks after the initial transplanting, we started tracking seedling survival (presented here) to investigate how seedlings responded to local habitat conditions. We conducted a seedling census for each of the 1200 tagged seedlings (12 seedlings per plot×100 plots), in early September 2022, which was two months at the end
Effects of food supplementation and helminth removal on space use and spatial overlap in wild bank vole populations
<p>Animal space use and spatial overlap can have important consequences for population-level processes such as social interactions and pathogen transmission. Identifying how environmental variability and inter-individual variation affect spatial patterns and in turn influence interactions in animal populations is a priority for the study of animal behavior and disease ecology. Environmental food availability and macroparasite infection are common drivers of variation, but there are few experimental studies investigating how they affect spatial patterns of wildlife. Bank voles (<em>Clethrionomys glareolus</em>) are a tractable study system to investigate spatial patterns of wildlife and are amenable to experimental manipulations. We conducted a replicated, factorial field experiment in which we provided supplementary food and removed helminths in vole populations in natural forest habitats and monitored vole space use and spatial overlap using capture-mark-recapture methods. Using network analysis, we quantified vole space use and spatial overlap. We compared the effects of food supplementation and helminth removal and investigated the impact of season, sex, and reproductive status on space use and spatial overlap. We found that food supplementation decreased vole space use while helminth removal increased space use. Space use also varied by sex, reproductive status, and season. Spatial overlap was similar between treatments despite up to three-fold differences in population size. By quantifying the spatial effects of food availability and macroparasite infection on wildlife populations, we demonstrate the potential for space use and population density to trade off and maintain consistent spatial overlap in wildlife populations. This has important implications for spatial processes in wildlife including pathogen transmission.</p>
Spatial patterns in neighbourhood effects on woody plant selection and bark stripping by deer in a lowland alluvial forest
<p>This dataset presents the incidence of bark stripping (present or not) and its intensity by two deer species mapped over all woody individuals ≥ 1 cm diameter at breast height (DBH). Stripping intensity was measured as the maximal percentage of the stripped stem circumference at the part of the stem with the horizontally widest stripping wound. A four-hectare square research plot is located in the Ranšpurk old-growth forest reserve in the south-eastern part of the Czech Republic (N48°40´, E16°56´).</p> <p>Several treefalls damaged the fence around the reserve in late autumn 2017, allowing fallow deer (<em>Dama dama</em> L.) and red deer (<em>Cervus elaphus</em> L.) to enter the reserve from the deer enclosure. The number of fallow deer and red deer individuals in the reserve was unknown, and likely fluctuated over time as they could enter and leave the reserve at any time. Data were collected in July 2018, ca 9–10 months after the fence was damaged. Although the fence was not fixed at the time of data collection (deer could still enter and leave the reserve), stripping wounds were not fresh and were likely received between late autumn 2017 and early spring 2018.</p> <p>The datasets includes tree and shrub individuals that fell within species-specific DBH range (susceptible individuals). The range was defined for each tree and shrub species as DBH<sub>min </sub>≤ DBH ≤ DBH<sub>max</sub>, where DBH<sub>min</sub> and DBH<sub>max</sub> are DBH of the smallest and largest stripped individuals. Individuals smaller and larger than this range were excluded from analyses, because small and large individuals may be relatively less often stripped. Woody species with ≥ 70 individuals are presented, because stochasticity does not allow meaningful spatial point pattern analyses with fewer individuals per species.</p> <p>Data contains the x and y coordinates of each individual in a local coordinate system, the woody species, its code, diameter at breast height, the incidence of stripping (present = 1 or not = 0), and the intensity of stripping (%).</p> <p> </p> <p> </p>
The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training
<p>This is the minimal dataset underlying the paper:</p> <p>"The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training"</p>
Figure 1 in Effect of initial infestation on population fluctuation and spatial distribution of Panonychus citri (Acari: Tetranychidae) on Thomson navel orange in Ghaemshahr, Iran
Figure 1. Population fluctuation of Panonychus citri on Thomson navel orange in a multi-treatment experiment in in 2016. Control treatment = average number of 0.48 mite per leaf; Treatment 1 = average number of 1.12 mites per leaf, Treatment 2 = average number of 1.23 mites per leaf, Treatment 3 = average number of 6.36 mites per leaf, Treatment
Figure 4 in Effect of initial infestation on population fluctuation and spatial distribution of Panonychus citri (Acari: Tetranychidae) on Thomson navel orange in Ghaemshahr, Iran
Figure 4. Population fluctuation of Panonychus citri on Thomson navel orange in a paired-treatment experiment in 2017. Infested treatment = average number of 0.79 mite per leaf, Control treatment = average number of 0.59 mite per leaf.
Figure 2 in Effect of initial infestation on population fluctuation and spatial distribution of Panonychus citri (Acari: Tetranychidae) on Thomson navel orange in Ghaemshahr, Iran
Figure 2. Population fluctuation of Panonychus citri on Thomson navel orange in a multi-treatment experiment in in 2016. Control treatment = average number of 0.2 mite per leaf, Treatment 1 = average number of 0.3 mite per leaf, Treatment
Development and evaluation of E3SM-MOSAIC: Spatial distributions and radiative effects of nitrate aerosol
<p>FC20TR-MOZ_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MZT_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_SLOW_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_MTC_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_WGT_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_MTC-SPLC_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_SPLC_PD</p> <p> </p> <p>NO3_TM_2005-2014.nc 10-yr mean nitrate burden</p> <p>NO3_AQCH_GAEX_2005-2014.nc 10-yr mean for nitrate chemistry production</p> <p>NO3_DRF_2005-2014.nc 10-yr mean nitrate direct forcing between PD and PI</p> <p>NO3_INDRF_2005-2014.nc 10-yr mean nitrate indirect forcing between PD and PI</p> <p> </p> <p>NH4_TM_2005-2014.nc 10-yr mean for ammonium burden</p> <p>NH4_DRF_2005-2014.nc 10-yr mean ammonium direct forcing between PD and PI</p> <p> </p> <p>SO4_TM_2005-2014.nc 10-yr mean for sulfate burden</p> <p>SO4_DRF_2005-2014.nc 10-yr mean sulfate direct forcing between PD and PI</p> <p> </p> <p>CCN3_1850.nc Cloud condensation nuclei number concentrations at 0.1% super saturation at PI</p> <p>CCN3_2005-2014.nc CCN3 at PD</p> <p>CCN3_NONO3_1850.nc CCN3 at PI without nitrate formation</p> <p>CCN3_NONO3_2005-2014.nc CCN3 at PD without nitrate formation</p> <p> </p> <p>CDNC_*.nc cloud droplet number concentrations</p> <p>CLDFRC_*.nc cloud fraction</p> <p>CWP_*.nc cloud liquid water path</p> <p> </p> <p> </p>
Supplementary material 1 from: Pontoppidan M, Nachman G (2013) Spatial Amphibian Impact Assessment – a management tool for assessment of road effects on regional populations of Moor frogs (Rana arvalis). Nature Conservation 5: 29-52. https://doi.org/10.3897/natureconservation.5.4612
Full model description following the protocol suggested by Grimm et al. (2006, 2010) and model parameterisation. (doi: 10.3897/natureconservation.5.4612.app). File format: Adobe PDF document (pdf).:
Fig. 2 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population
Fig. 2. Cluster analyses of imperial eagle breeding areas based on prey composition data. Region codes are presented in Fig. 1. Codes with bold characters represent mountainous habitats. The single breeding pair of the Cserehát Mountains was excluded from the analysis, because of low sample size
Fig. 3 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population
Fig. 3. Frequency of the three main prey species (a-c) and reproductive success (d) of imperial eagles in two East-Hungarian regions. Boxplots presents the minimum-maximum (whiskers), lower and upper quartiles (box) and the median (line) of the data. Dots are outliers. Significance of difference is in-
Fig. 2 in Relationships between morphology, diet and spatial distribution: testing the effects of intra and interspecific morphological variations on the patterns of resource use in two Neotropical Cichlids
Fig. 2. Head of Satanoperca pappaterra (a) and Crenicichla britskii (b), showing differences in the mouth protrusion.
Figure 6 in Natural and human effects on harbor seal abundance and spatial distribution in an Alaskan glacial fjord
Figure 6. Estimated area of Disenchantment Bay (km2) containing three different ice cover types: scattered (1–3 tenths), intermediate (4–6 tenths), and dense (7–10 tenths), and all types combined (i.e., ice-covered area [ICA]) from 3 May to 4 August 2002. Estimates of ice cover were averaged within grid cells (when n> 1) and the areas of cells with each type of ice cover were summed (Jansen et al. 2006)) and then scaled upward (proportionately) based on the percent of the study area that was sampled on a given day.
Figure 7 in Natural and human effects on harbor seal abundance and spatial distribution in an Alaskan glacial fjord
Figure 7. Patterns of ship movement and visitation time in Disenchantment Bay, Alaska, in 2002 (n = 56 cruise ships of 105 total during study). Shading of cells represents the cumulative time that visiting ships spent within that cell for each of three months: May, June, and July (including early August). Four distinct shades, from gray to black, reflect increasing residence: <5 min, 5–10 min, 10–20 min,>20 min, respectively. Refer to Figure 1 for geographical points and scale.
Figure 5 in Natural and human effects on harbor seal abundance and spatial distribution in an Alaskan glacial fjord
Figure 5. Standardized resource selection coefficient by harbor seals for ice cover class in Disenchantment Bay, Alaska, 3 May to 4 August 2002, for the Bernoulli part of the P1B model (i.e., for the cell-based abundance of seals). The solid circles and lines are for all seals, and the open circles and dashed lines are for mother-pup pairs. Confidence intervals (95%) are shown by the vertical bars. The thin horizontal line represents equal selection for all ice cover classes.
Figure 4 in Natural and human effects on harbor seal abundance and spatial distribution in an Alaskan glacial fjord
Figure 4. Standardized resource selection coefficient by harbor seals for ice cover class in Disenchantment Bay, Alaska, 3 May to 4 August 2002, for the Bernoulli part of the P1B model (i.e., for the cell-based spatial distribution of seals). The solid circles and lines are for all seals, and the open circles and dashed lines are for mother-pup pairs. Confidence intervals (95%) are shown by the vertical bars. The thin horizontal line represents equal selection for all ice cover classes.
Figure 3 in Natural and human effects on harbor seal abundance and spatial distribution in an Alaskan glacial fjord
Figure 3. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys () and the previous day () in Disenchantment Bay, Alaska, on (A) 6 May, (B) 16 May, (C) 31 May, (D) 20 June, (E) 18 July, and (F) 4 August 2002 (figures for all 18 survey dates are available as supplemental material online). The time of day that ships reached their maximum penetration appears near the location symbol. The range of seal counts summed per grid cell is shown in three levels: small dot (<5 seals), medium dot (5–20 seals), and large dot (>20 seals). A small, overlying white dot indicates the presence of at least one mother-pup pair within that grid cell. Ice cover is represented by a gradient in cell-color shading: light gray (scattered), medium gray (intermediate), dark gray (dense). For this graphic, if cells with no ice data were bounded on three sides by cells with ice measures, the average of neighboring cells was used as an estimate. Refer to Figure 1 for geographical points and scale.
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.