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227 results for “range size”
Dust mass fractions for dust bins covering the 0.1 to 100 µm size range
<p>This is a file containing the dust mass fractions for dust bins covering the 0.1 to 100 µm size range calculated from the BFT-supercoarse emitted dust PSD parameterization (Meng et al., 2021 GRL submitted). </p>
Data and Code for the paper 'Indication of long-range correlations governing city size'
<div> <h1>Summary</h1> <p>This repository contains the preprocessed data necessary for constructing the city network as described in the related paper, as well as the code to do the Shortest-path Fluctuation Analysis (SFA) on those networks.</p> <div> <h2>Under the <code>data</code> folder</h2> <ul> <li> <p>In the <code>Node_list</code> folder, each <em><code>CSV</code></em> file has the name convention like <code>AL_1000_node_list.csv</code>, for example, this means the table contains the list of <strong>nodes</strong> that make up the network for <strong>Austria</strong> (as country code, <code>AL</code>) at the spatial clustering distance threshold of <strong>1000</strong>m. The table has 3 columns with column names, and without row names.</p> <ul> <li> <p>Each row in the table is a record of one node, the <strong><em>node ID</em></strong> is the <code>row_id</code> of the record in the table, the first record has a row_id of <strong>0</strong>.</p> </li> <li> <p>The <strong>first</strong> column in the table is the <em><code>X</code></em> coordinate of the mass center of the node.</p> </li> <li> <p>The <strong>second</strong> column in the table is the <em><code>Y</code></em> coordinate of the mass center of the node.</p> </li> <li> <p>The <strong>third</strong> column in the table is the <strong>Size</strong> of the node, i.e., the number of pixels of this city.</p> </li> </ul> </li> <li> <p>In the <code>Edge_list</code> folder, each <em><code>TXT</code></em> file has the name convention like <code>AL_1000_edges.txt</code>, for example, this means the table contains the list of <strong>edges</strong> that make up the network for <strong>Austria</strong> (as country code, <code>AL</code>) at the spatial clustering distance threshold of <strong>1000</strong>m. The table has 2 columns without column name, without row name.</p> <ul> <li> <p>Each row in the table is a record of one edge that is composed of a pair of nodes, the <strong><em>node ID</em></strong> is the <code>row_id</code> of that node in the <strong>node_list</strong> table.</p> </li> <li> <p>The <strong>first</strong> column in the table is the <strong><em>ID</em></strong> of the node on one side of an edge.</p> </li> <li> <p>The <strong>second</strong> column in the table is the <strong><em>ID</em></strong> of the node on the other side of an edge.</p> </li> </ul> </li> </ul> </div> <div> <h2>Under the <code>code</code> folder</h2> <ul> <li> <p>The <code>SFA_args_LSPT_out.cpp</code> file contains the <strong>C++</strong> code to do the SFA calculation, detailed information can be found in the documentation of the code file.</p> </li> <li> <p>The <code>SFA_config.ini</code> file contains some configuration parameters for running the compiled program, details can also be found in the file. This file has to be put in the same folder as the compiled executable file.</p> </li> </ul> </div> </div>
Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (Raw data)
<p>Datasets for the analysis developed in the Article "<em><strong>Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs</strong></em>". For more information, please refer to the original publication.</p> <p>Network_Structural_Index_&_SpogeTraits.csv <- Structural Index for the sponge-dwelling fauna network, sponge accumulated area and sponges’ morphology.</p> <p>NWTA_CoralReefs_Sponges_ interactions.csv <- Relationship between host sponges and guest fauna in the Northwester Atlantic coral reefs</p> <p>NWTA_CoralReefs_Sponge_reacords.csv <- Sponge species incidence records in the Northwester Atlantic coral reefs</p> <p>sponges_morphological_description.csv <- Sponge morphological standardization</p> <p>Network.html <- Interactive sponge-dwelling fauna network</p> <p>Enjoy!<br> </p>
Range size and local abundance data for angiosperm communities across an elevation gradient, Rocky Mountain Biological Lab, 2021-2022
This dataset contains abundance and range size data for angiosperm communities at three sites in Washington Gulch near the Rocky Mountain Biological Laboratory (RMBL, Gothic, Colorado, USA) for 2021 and 2022. RMBL is located in the East River valley of the West Elk mountains, approximately 10 kilometers from Crested Butte, Colorado. Study sites were located at 2815 m (38°53'50"N, 106°58'43"W), 3165 m (38°57'38"N, 107°01'53"W) and 3380 m (38°58'10"N, 107°01'53"W) in elevation, and contained five 1.2 m x 1.2 m plots each. We identified all vascular plants to species level. Each plot was sampled once per year near the peak of the growing season (approximately mid-July, depending on the year and elevation). In each plot, we counted all individuals of every species. To quantify abundance, we averaged local abundance across all five plots at each site and the two data collection years, and then ranked species by averaged abundance within each site (highest to lowest). We calculated range size as Extent of Occurrence (EOO) and Area of Occupancy (AOO). We calculated AOO and EOO with GBIF data using the ‘red’ package. We then ranked species by AOO within each site (largest to smallest).
Soil Particle Size Analysis at Permanent Quadrat locations, Jornada Experimental Range, 2001-2020
This completed dataset, from samples collected in 2001 and 2020, contains soil particle size analysis (PSA) and sand fractionation data from soil cores collected at 117 quadrat locations that are part of the Jornada Experimental Range's long-term Permanent Quadrats study. The goal of this effort was to help characterize plant-scale factors related to vegetation dynamics observed in the Permanent Quadrats. At each quadrat location, 4 cores were collected at 2 depths (0-5cm and 5-20cm) and assessed for percent sand, silt and clay. The sand fraction, if large enough, was then separated into 5 sand size classes (53-106 micrometers, 106-250 micrometers, 250-500 micrometers, 500-1000 micrometers, 1000-2000 micrometers) to measure the percent fraction of each. Long term vegetation data from this study are available in data packages knb-lter-jrn.210351001 and knb-lter-jrn.210351002.
Data from: The evolution of environmental tolerance and range size: A comparison of geographically restricted and widespread Mimulus
<p>The geographic ranges of closely related species can vary dramatically, yet we do not fully grasp the mechanisms underlying such variation. The niche breadth hypothesis posits that species that have evolved broad environmental tolerances can achieve larger geographic ranges than species with narrow environmental tolerances. In turn, plasticity and genetic variation in ecologically important traits and adaptation to environmentally variable areas can facilitate the evolution of broad environmental tolerance. We used five pairs of western North American monkeyflowers to experimentally test these ideas by quantifying performance across eight temperature regimes. In four species pairs, species with broader thermal tolerances had larger geographic ranges, supporting the niche breadth hypothesis. As predicted, species with broader thermal tolerances also had more within-population genetic variation in thermal reaction norms and experienced greater thermal variation across their geographic ranges than species with narrow thermal tolerances. Species with narrow thermal tolerance may be particularly vulnerable to changing climatic conditions due to a lack of plasticity and insufficient genetic variation to respond to novel selection pressures. Conversely, species experiencing high variation in temperature across their ranges may be buffered against extinction due to climatic changes because they have evolved tolerance to a broad range of temperatures.</p>
Datasets and R codes used for the analyses in "Seasonal variation in home range size of White-Backed Woodpeckers"
<p><strong>Abstract</strong></p> <p>Knowing a species’ area requirements is fundamental for species conservation. For the nominate subspecies of the White-backed Woodpecker<em> Dendrocopos leucotos</em>, a species of high conservation concern in Europe, estimates of the seasonal and year-round area requirements based on telemetry are missing. In the present study, we radio-tracked adult White-backed Woodpeckers in Central Europe and investigated bi-monthly home range sizes based on three home range estimators in relation to season, sex, body weight, and year. Home range size of 49 radio-tracked individuals varied depending on the used home range estimator, with minimum convex polygons (MCP) and autocorrelated kernel density estimation (AKDE) producing 1.6 – 1.8 and 2 – 3.3 times larger seasonal home ranges than traditional kernel density estimation (KDE). Moreover, home range sizes varied between seasons. Home ranges were smallest in February/March (predicted median home range sizes ranged from 35 ha with KDE to 88 ha with AKDE) and April/May (KDE: 30 ha, AKDE: 55 ha) and larger during the rest of the year (KDE: 48 – 67 ha, AKDE: 136 – 184 ha). The mean home range size of six individuals tracked in all seasons (calculated with all locations per individual) was 116 ha with KDE, 304 ha with MCP and 350 ha with AKDE. Our results highlight the importance of considering the full annual cycle when addressing area requirements of White-backed Woodpeckers and likely also of other species. Furthermore, our study shows that using multiple methods for home range estimation may be useful to obtain results that are both comparable with those of other studies and capture the range in which the true home range size is likely to be. For the conservation of the White-backed Woodpecker, we conclude that at least 116 to 350 ha of forest should be present for a pair.</p>
Data and R codes: species range-size variation in oaks
<p>We used occurrence data of 183 oak species (<em>Quercus </em>spp.) in North and South America to test how niche breadth and niche position affect the amount of suitable habitat area, and how colonization ability and post-glacial migration lags affect range filling. This dataset includes the data and R files related to the analyses. </p>
Data and code for: Grain size of fluvial gravel bars from close-range UAV imagery – uncertainty in segmentation-based data
<p>UAV images used for SfM model generation and all images (both SI and OM), in which we measured grain sizes. The code used for image processing and uncertainty estimation of grain size distributions as python files and executable jupyter notebooks, where the latter also serve as documentation.</p>
Diversification in the Rosales is influenced by dispersal, geographic range size, and pre-existing species richness
<p>Biodiversity results from origination and extinction; thus there is interest in determining those traits that influence this balance. Among traits implicated in the success or failure of lineages are dispersal, colonization ability, and geographic range size. We investigate the impact of dispersal and range size on contemporary diversity in the order Rosales.</p> <p> We use the MuSSE method to explore the effects on genus-level diversification of two genus-level traits (geographic range size and within-genus proclivity to speciate), and two species traits (seed dispersal and growth habit). We then used MuHiSSE for species-level associations. Finally, we conducted a PGLS (phylogenetic least-squares) analysis to distinguish between speciation within genera versus origination of new genera.</p> <p>At the species-level, animal dispersal enhances diversification rate in both woody and herbaceous lineages, while woody lineages without animal dispersal have higher extinction rates than speciation rates. At the genus level, herbaceous taxa have positive diversification rates regardless of other character states. Diversification rate variation is also explained by two interactions: (1) a three-way interaction between large geographic range, animal-mediated dispersal, and high within-genus species richness, whereby genera possessing all three traits have high diversification rates, and (2) a four-way interaction by which the three-way interaction is stronger in woody genera than in herbaceous genera.</p> <p>Colonization ability may underlie the relationship between dispersal type and range size and may influence past diversification rates by decreasing extinction rates during late Cenozoic times of climate volatility. Thus, colonization ability could be used to predict future extinction risk to improve conservation success.</p> <p>Please be aware that if you ask to have your user record removed, we will retain your name in the records concerning manuscripts for which you were an author, reviewer, or editor. In compliance with data protection regulations, you may request that we remove your personal registration details at any time. (Use the following URL: https://www.editorialmanager.com/ajb/login.asp?a=r). Please contact the publication office if you have any questions.</p>
Text-fig. 1. Bivariate diagram of length and width of the upper dentition of selected European small and middle size Amphicyoninae compared with the Tuchořice specimens. a: P4; b: M1; c: M2; d: m1; e: m2. Data from Schlosser (1899, 1904), Thenius (1949), Dehm (1950), Heizmann (1973), Ginsburg (1977, 1989), Peigné (2012). Dotted line – ranges of maximum and minimum values from the average of teeth of Cynelos lemanensis from Ulm (Peigné and Heizmann 2003). Abbreviations: L – length; W – width. in The Amphicyoninae (Amphicyonidae, Carnivora, Mammalia) Of The Early Miocene From Tuchořice, The Czech Republic
Text-fig. 1. Bivariate diagram of length and width of the upper dentition of selected European small and middle size Amphicyoninae compared with the Tuchořice specimens. a: P4; b: M1; c: M2; d: m1; e: m2. Data from Schlosser (1899, 1904), Thenius (1949), Dehm (1950), Heizmann (1973), Ginsburg (1977, 1989), Peigné (2012). Dotted line – ranges of maximum and minimum values from the average of teeth of Cynelos lemanensis from Ulm (Peigné and Heizmann 2003). Abbreviations: L – length; W – width.
No evidence for the consistent effect of supplementary feeding on home range size in terrestrial mammals
<p>Food availability and distribution are key drivers of animal space use. Supplemental food provided by humans can be more abundant and predictable than natural resources. It is thus believed that supplementary feeding modifies the spatial behaviour of wildlife. Yet, such effects have not been tested quantitatively across species. Here, we analysed changes in home range size due to supplementary feeding in 23 species of terrestrial mammals using a meta-analysis of 28 studies. Additionally, we investigated the moderating effect of factors related to i) species biology (sex, body mass, taxonomic group), ii) feeding regimen (duration, amount, purpose), and iii) methods of data collection and analysis (source of data, estimator, spatial confinement). We found no consistent effect of supplementary feeding on changes in home range size. While an overall tendency of reduced home range was observed, moderators varied in the direction and strength of the trends. Our results suggest that multiple drivers and complex mechanisms of home range behaviour can make it insensitive to manipulation with supplementary feeding. The small number of available studies stands in contrast with the ubiquity and magnitude of supplementary feeding worldwide, highlighting a knowledge gap in our understanding of the effects of supplementary feeding on ranging behaviour.</p>
Figure 5 in Red deer on the move: home range size and mobility in Bulgaria
Figure 5. Comparison between male and female red deer mobility. Boxes – the interquartile range (25-75 percentiles); middle line in boxes – median values; diamonds – average values; whiskers – minimum and maximum values within the 95.0% confidence level; circles – outliers; the perimeter outside boxes shows the probability density of the of the 12 hours step-length displacement in males and females.
Figure 3 in Red deer on the move: home range size and mobility in Bulgaria
Figure 3. Comparison of the core and total area in males and females. Boxes – the interquartile range (25-75 percentiles); middle line in boxes – median values; diamonds – average values; whiskers – minimum and maximum values within the 95.0% confidence level; circles – outliers; circles with plus sign - "Far outside" outliers, points more than 3 times above the interquartile range.
Figure 1. Study area and 100 in Red deer on the move: home range size and mobility in Bulgaria
Figure 1. Study area and 100 % minimum convex polygons from the locations of the GPS-collared red deer
Fig. 1 in A Study Of The Changes In The Range Sizes Of White-Vented Mynas In Singapore
Fig. 1. Map of Singapore showing localities of seven white-vented mynas radiotracked in Singapore from 8 November 2001 to 14 January 2002.
Elevational range size patterns of vascular plants in Himalaya contradict Rapoport's rule
<p>1. Elevational range size patterns reflect ecological and evolutionary processes, but they are also affected by geometric constraints. The confounding effect of these constraints led to an ongoing controversy about the elevational Rapoport's rule, which postulates a positive association between the range size and elevation, and about the plausibility of the climate variability hypotheses as its causal explanation.</p> <p>2. Here we used an advanced null modelling approach to disentangle the interacting effects of geometric constraints and species richness gradients on the elevational range size of vascular plants. We collected extensive field data on elevational distribution for 728 vascular plant species occurring in the Ladakh region, Western Himalaya. We supplied these regional data with sub-continental elevational ranges extracted from the literature. Moreover, we used in-situ measured temperatures to quantify temperature variability along an elevational gradient to test the climate variability hypothesis.</p> <p>3. Observed range size patterns were sensitive to methods used to quantify the average range size. Range truncation disproportionately affected regional ranges of low-elevation species and resulted in spurious support of elevational Rapoport's rule. However, when the confounding effects of domain boundaries and richness gradient were controlled, our null models revealed only slight deviations from the random expectations of elevational range size patterns, contrasting with the prediction of the Rapoport's rule. In line with these findings, seasonal and diurnal temperature variability did not change with elevation.</p> <p>4. Synthesis: Geometric constraints combined with underlying species richness gradient create range size patterns seemingly supporting Rapoport´s elevational rule. However, null models accounting for these effects indicate that the range-size of vascular plants in the Himalayas does not increase with elevation. Given the universality of the geometric constraints and species richness gradient, our results suggest that these confounding factors must be controlled when testing Rapoport's rule. The null model approach described here provides an efficient tool to do that.</p>
Fig. 1 in Home range size and microhabitat selection by a tropical partridge species in moist evergreen forest
Fig. 1. Analysis of green-legged partridges' group range based on radio locations using the characteristic hull polygon (CHP) and minimum convex polygon (MCP; 100%, 95% and 50%) methods. F refers to females, and M refers to males.
Fig. 1 in Preliminary estimation of home range size for Meristogenys orphnocnemis, a common Bornean Ranid, in an altered forest ecosystem using radiotelemetry
Fig. 1. Section of stream in SAFE Project experimental site, known as logged forest edge (LFE) stream, where all radiotracking occurred.
Home range use in the West Australian seahorse Hippocampus subelongatus is influenced by sex and partner's home range but not by body size or paired status
<p><span>These data and scripts form the basis for </span>Kvarnemo C, Andersson SE, Elisson J, Moore GI and Jones AG (2021). Home range use in the West Australian seahorse <em>Hippocampus subelongatus</em> is influenced by sex and partner's home range but not by body size or paired status. Journal of Ethology 39: 235–248. https://doi.org/10.1007/s10164-021-00698-y. The abstract below is from this paper:</p> <p>Genetic monogamy is the rule for many species of seahorse, including the West Australian seahorse Hippocampus subelongatus. In this paper, we revisit mark-recapture and genetic data of H. subelongatus, allowing a detailed characterization of movement distances, home range sizes and home range overlaps for each individual of known sex, paired status (paired or unpaired) and body size. As predicted, we find that females have larger home ranges and move greater distances compared to males. We also confirm our prediction that the home ranges of pair-bonded individuals (members of a pair known to reproduce together) overlap more on average than home ranges of randomly chosen individuals of the opposite or same sex. Both sexes, regardless of paired status, had home ranges that overlapped with, on average, 6–10 opposite-sex individuals. The average overlap area among female home ranges was significantly larger than the overlap among male home ranges, probably reflecting females having larger home ranges combined with a female biased adult sex ratio. Despite a prediction that unpaired individuals would need to move around to find a mate, we find no evidence that unpaired members of either sex moved more than paired individuals of the same sex. We also find no effect of body size on home range size, distance moved or number of other individuals with which a home range overlapped. These patterns of movement and overlap in home ranges among individuals of both sexes suggest that low mate availability is not a likely explanation for the maintenance of monogamy in the West Australian seahorse.</p>
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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.
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DANDI Archive for NWB datasets
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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.