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8,729 results for “Ranges”
Assessing the links between pollinators and the genetic and epigenetic features of plant species with contrasting distribution ranges
<p>In flowering plants, pollinators contribute to gene flow while they also respond to variation in plant traits together determined by genetic, epigenetic and environmental sources of variation. Consequently, a correlation between abundance and diversity of pollinators and the genetic and epigenetic characteristics of plant populations such as diversity or distinctiveness is expected. However, no study has explored these long-term dimensions of plant-pollinator interactions. Mediterranean narrow endemics often exhibit unexpectedly high levels of population genetic and epigenetic diversity. We hypothesize that pollinators may contribute to explain this pattern. Specifically, given the higher sensitivity of small, isolated population to gene flow, we expect a stronger association of pollinators with population genetic and epigenetic variability in narrow endemics than in widely distributed congeners. We studied five pairs of congeneric plant species, consisting of one narrow endemic with a restricted distribution and one widespread congener, found in the Sierra de Cazorla mountains (SE Spain). We characterized the pollinators in up to three populations per species to estimate their diversity and visitation rates. Additionally, we calculated the genetic and epigenetic diversity and distinctiveness of each population using AFLP markers and methylation-sensitive AFLP markers (MSAP), respectively. We assessed the relationship between pollinator diversity and visitation rates. The diversity of pollinators did not vary according to the plant´s distribution range, but visitation rate was higher in widespread species. As predicted, only narrow endemics showed a significant association between pollinators and their population genetic and epigenetic characteristics. Specifically, higher pollinator diversity and visitation rates entailed higher population genetic diversity and lower epigenetic distinctiveness. This work shows the importance of investigating the relationship between pollinator diversity and population genetics and epigenetics to better understand the evolution of plant rarity.</p>
Accelerometer, gyroscope and pressure data associated with behaviors of free-ranging hawksbill sea turtles (Eretmochelys imbricata)
<p> </p> <p> </p> <div> <div> <div> <div> <div> <p>In this paper, we explored the use of transfer learning across species and taxa, employing fully convolutional neural networks to predict the behaviors of critically endangered hawksbill sea turtles from acceleration data. For this purpose, fully convolutional neural networks (V-net and U-net) were pre-trained on a dataset of green turtles (Zenodo link) and human data (Intensive Care Unit (ICU) HAR dataset, <a href="https://doi.org/10.24432/C54S4K" target="_new" rel="noreferrer">https://doi.org/10.24432/C54S4K</a>) before being fine-tuned on the hawksbill dataset. The results reveal a 8% and 4% improvement in F1-score with transfer learning from the green turtle and human datasets, respectively, compared to training the models from random weight initialization (without transfer learning). </p> </div> </div> </div> </div> </div> <p> </p> <p>The dataset comprised the raw acceleration, gyroscope and depth sequence of 6 free-ranging hawksbill sea turtles associated with the behaviors. The indiviuals were equipped with a on-board video recorder combined with an accelerometer, gyroscope, magnetometer and luminosity, temperature and depth sensors using four suction cups and an automatic release system over a two-day periods (see Jeantet et al. 2020 for details and the associated article). The accelerometer, gyroscope, magnetometer recorded at 20 Hz and the pressure, temperature and luminosity sensors at 1 Hz. The cameras were programmed to record until nightfall (6 pm) and resume at daybreak (6 am). The magnetometer, luminosity and temperature data are provided but not used in the associated study. </p> <p> </p> <div> <div> <div> <div> <div> <p>For each individual, the data collected by the devices was correlated with observed behaviors from video recordings. Unlabeled sequences, mostly comprising night recordings, were excluded, resulting in the creation of one file per day of deployment for each individual. </p> </div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <p>To process the depth data and increase the sampling rate to 20 Hz, we used a linear interpolation technique. We called this new variable "Pressure_corr". Additionally, we calculated the pressure difference ("Pressure_diff") between each measuring point (originally at 1 Hz).</p> </div> </div> </div> </div> </div> <p> </p> <p>"In total, 69.7 hours of multi-sensor sequences were labelled from six different hawksbill turtles (approximately 11.6 hours of recording per individual, max = 17.8 hours, min = 6.3 hours, standard deviation = 3.6 hours). The predominant behavior observed in the videos was <em>Feeding</em>, totaling over 38.6 hours, followed by <em>Resting</em> and <em>Swimming</em>, with 19.1 hours and 7.9 hours, respectively. The other behaviors were expressed in minority (<em>Breathing</em>: 2.2 hours, <em>Gliding</em>: 1 hour, <em>Scratching</em>: 0.8 hour and <em>Other</em>: 0.1 hour). " </p> <p> </p> <p>The folder contains 10 Python matrices, each with 15 columns (AccX, AccY, AccZ, GyrX, GyrY, GyrZ, MagX, MagY, MagZ, Depth, Light, Temperature, Pressure_corr, Pressur_diff, Behavior) and a number of rows corresponding to the deployment duration. The title of each file indicates the camera number used (CC-09-XX) and the deployment day (DD-MM-YYYY), with the last digit specifying whether the matrix corresponds to the first or second day of deployment.</p> <p> </p> <p>The folder also contains two dictionaries (behInd_to_behName, behName_to_behInd) that specify the behaviors associated with each number used as a label in the Behavior column. Additionally, there is a dictionary (dico_info) that provides the names of the matrix columns and the frequence of recording.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Data for isolation-by-environment and its consequences for range shifts with global change: Landscape genomics of the invasive common tansy
<p>Invasive species are a growing global economic and ecological problem. However, it is not well understood how environmental factors mediate invasive range expansion. In this study, we investigated the recent and rapid range expansion of common tansy across environmental gradients in Minnesota, U.S.A. We densely sampled individuals across the expanding range and performed reduced representation sequencing to generate a dataset of 3071 polymorphic loci for 176 individuals. The dataset includes additional samples from the native range in Finland that were not used in the downstream analysis but are contributed for completeness. The dataset includes the genotype calls for all individuals sampled and sequenced. The genotype file was generated by stacks2.59 running the denovo pipeline and then using the populations function where we kept loci that were in 70% of populations and had a minor allele frequency of at least 1%. We used non-spatial and spatially-explicit analyses to determine the relative influences of geographic distance and environmental variation on patterns of genomic variation. We found no evidence for isolation-by-distance (IBD) but strong evidence for isolation-by-environment (IBE), indicating that environmental factors may have modulated patterns of range expansion.</p>
Распространение средиЗемноморской мидии Mytilus galloprovincialis Lamarck, 1819 в Японском море. in The extension of the distributional range of an invasive mussel, Mytilus galloprovincialis (Bivalvia: Mytilidae) in the Sea of Japan
Распространение средиЗемноморской мидии Mytilus galloprovincialis Lamarck, 1819 в Японском море.
Data from: Dietary plasticity and broad North Atlantic origins inferred from bulk and amino acid-specific δ15N and δ13C favor killer whale range expansions into Arctic waters
<p>Killer whales (<em>Orcinus orca</em>) occur seasonally in the eastern Canadian Arctic (ECA), where their range expansion associated with declining sea ice have raised questions about the impacts of increasing killer whale predation pressure on Arctic-endemic prey. We assessed diet and distribution of ECA killer whales using bulk and compound specific stable isotope analysis (CSIA) of amino acids (AA) of 54 skin biopsies collected from 2009-2020 around Baffin Island, Canada. Bulk ECA killer whale skin δ15N and δ13C values did not overlap with potential Arctic prey after adjustment for trophic discrimination, and instead reflected foraging history in the North Atlantic prior to their arrival in the ECA. Adjusted killer whale stable isotope (SI) values primarily overlapped with several species of North Atlantic baleen whales or tuna. Amino acid (AA)-specific δ15N values indicated the ECA killer whales fed primarily on marine mammals, having similar glutamic acid δ15N – phenylalanine δ15N (δ15NGlx-Phe) and threonine δ15N (δ15NThr) as mammal-eating killer whales from the eastern North Pacific (ENP) that served as a comparative framework. However, one ECA whale grouped with the fish-eating ENP ecotype based δ15NThr. Distinctive essential AA δ13C of ECA killer whale groups, along with bulk SI similarity to killer whales from different regions of the North Atlantic, indicate different populations converge in Arctic waters from a broad source area. Generalist diet and long-distance dispersal capacity favor range expansions, and integration of these insights will be critical for assessing ecological impacts of increasing killer whale predation pressure on Arctic-endemic species.</p>
Data from: Local climate change velocities and evolutionary history explain multidirectional range shifts in a North American butterfly assemblage
<p>Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonize new suitable climatic niches. However, from 18 years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards the region that is warming the fastest (southeast). Butterflies shifted their centroids at a mean rate of 4.87 km yr-1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges. Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity. Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as a metric for dispersal capability) were not correlated with the rate at which species shifted their ranges. We observed a high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges. This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.</p>
High-power in-phase and anti-phase mode emission from linear arrays of resonant-tunneling-diode oscillators in the 0.4-to-0.8-THz frequency range - data
<p>Experimental and simulation data from the paper "High-power in-phase and anti-phase mode emission from linear arrays of resonant-tunneling-diode oscillators in the 0.4-to-0.8-THz frequency range".</p>
Movement of juvenile migratory birds from settlement to adulthood across the non-breeding range
<p>Among migratory vertebrates, high levels of fidelity to non-breeding sites during adulthood are common. If occupied sites vary in quality, strong site-fidelity can have profound consequences for individual fitness and population demography. Given the prevalance of adult site-fidelity, the regions of the non-breeding range to which juveniles first migrate, and the scale of any subsequent movements, are likely to be pivotal in shaping distributions and demographic processes across population ranges. However, inherent difficulties in tracking migratory individuals through early life mean that opportunities to quantify juvenile settlement and movements across non-breeding ranges, and the mechanisms involved, are extremely rare.Through long-term, range-wide resightings of hundreds of colour-marked individuals from their first migration to adulthood, and application of state-space models, we quantify levels of juvenile and adult regional-scale movements and distances at different life stages across the whole non-breeding distribution range in a migratory shorebird, the Black-tailed Godwit (<em>Limosa limosa islandica</em>). We show that the probability of individuals changing non-breeding regions (seven historical wintering regions spanning the Western Europe range) at all ages are very low (mean movement probability = 10.9% from first to subsequent winter, and 8.3% from first adult winter to later winters). Movement between regions was also low between autumn and winter of the same year for both juveniles (mean movement probability = 17.0%) and adults (10.4%). The great majority of non-breeding movements from the first autumn to adulthood were within regions and less than 100 km. The scarcity of regional-scale non-breeding movements from the first autumn to adulthood means that the factors influencing where juveniles settle will be key determinants of non-breeding distributions and of the rate and direction of changes in distributions.</p>
Fig. 12 in Changes in the range of Pterostichus melas and P. fornicatus (Coleoptera, Carabidae) on the basis of climatic modeling
Fig. 12. Map of comparison of P. melas current range and ranges for 2050 and 2070
Fig. 11 in Changes in the range of Pterostichus melas and P. fornicatus (Coleoptera, Carabidae) on the basis of climatic modeling
Fig. 11. Comparison of P.melas current range and range for 2050
Fig 3 in Range extension of buckler crab, Cryptopodia angulata (Decapoda: Brachyura: Parthenopidae) from Karwar coast (Arabian Sea), Karnataka, India
Fig 3: Cryptopodia angulata: ventral view
Fig 1 in Range extension of buckler crab, Cryptopodia angulata (Decapoda: Brachyura: Parthenopidae) from Karwar coast (Arabian Sea), Karnataka, India
Fig 1: Map showing the location of the area in Karwar coast (* -Majali coast).
Artifact for research regarding Ranged Program Analysis
<div> </div> <div>This artifact is a summary of data regarding ranged program analysis.</div> <div>It contains the most important results from the following three papers:</div> <p> </p> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Parallel Program Analysis via Range Splitting”. In: Proc. FASE. Vol. 13991. 2023, pp. 195–219. doi: 10.1007/978-3-031-30826-0_11.</div> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Ranged Program Analysis via Instrumentation”. In: Proc. SEFM. Vol. 14323. 2023, pp. 145–164. doi: 10.1007/978-3-031-47115-5_9.</div> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Parallel program analysis on path ranges”. In: Sci. Comput. Program. 238 (2024). doi: 10.1016/j.scico.2024.103154.</div> <p> </p> <div>More precisely, it contains all the results from the PhD-thesis of Jan Haltermann.</div> <div>In more detail, it contains all experimental data collected during the experiments, the run-configs to re-run the experiments, the instructions on how to regenerate the BenchExec tables that are used for analysis of the data, and the scripts to reconstruct all the findings from the thesis.</div> <p> </p> <div>It is structured as follows:</div> <div>- `configs` contains all the BenchExec run configs needed to rerun the experiments.</div> <div>- `data` contains the raw data collected during the experiments.</div> <div>- `figures` contains the generated figures</div> <div>- `macros` contains the macros for the Latex document with the evaluation results</div> <div>- `overview-table.xml` is needed to generate the BenchExec result tables.</div> <div>- `scripts` contains the scripts to analyze the results and generate the figures</div> <div>- `tables` contains the tables generated using the raw data and are used for analyzing the results</div> <div>- `used-tools` contains the executables of the tools used for the evaluation (in this case only CPAchecker)</div> <div>- `validation_of_incorrect_results.zip` contains the results of the manual analysis of the incorrect alarms generated, as explained in the paper.</div> <p> </p> <div>The version of CoVeriTeam used can be found [on GitLab](https://gitlab.com/sosy-lab/software/coveriteam/-/tree/rangedAnalysis?ref_type=heads) </div> <div>The latest source code of CPAchecker used can be found [on GitLab](https://gitlab.com/sosy-lab/software/cpachecker/-/tree/ranged_program_analysis)</div> <p><br><br><br><br></p>
Fig. 3 in Spatial Organization And Home Range Of Apodemus Flavicollis And A. Agrarius On Mt. Avala, Serbia
Fig. 3. Home range (HR) areas of A. flavicollis and A. agrarius
Fig. 2 in Spatial Organization And Home Range Of Apodemus Flavicollis And A. Agrarius On Mt. Avala, Serbia
Fig. 2. Observed range length (ORL) values of A. flavicollis and A. agrarius
Data Set for Self-adapting short-range correlation functional for complete active space-based approximations
<p>Data Set to accompany:</p> <p> Self-adapting short-range correlation functional for complete active space-based approximations</p>
Data from: Age-related physiological dysregulation progresses slowly in semi-free-ranging chimpanzees
<p>Lifestyle has widespread effects on human health and aging. Prior results from chimpanzees, one of the closest evolutionary relatives of humans, indicate that these lifestyle effects may also be shared with other species, as semi-free-ranging chimpanzees fed a naturalistic diet show healthier values in several specific health biomarkers, compared with their sedentary, captive counterparts. Here, we examined how lifestyle factors associated with different environments affect rates of physiological aging in closely related chimpanzees (<em>Pan troglodytes</em>). We compared physiological dysregulation, an index of biological aging, in semi-free-ranging chimpanzees in an African sanctuary versus captive chimpanzees in US laboratories. If the rate of aging is accelerated by a high-calorie diet and sedentism, we predicted greater age-related dysregulation in the laboratory populations. Conversely, if the costs of a wild lifestyle accelerate aging, then semi-free-ranging chimpanzees at the sanctuary, whose environment better approximates the wild, should show greater age-related dysregulation. We further tested whether dysregulation differed based on sex or body system, as in humans. We found that semi-free-ranging chimpanzees showed lower overall dysregulation, as well as lower age-related change in dysregulation, than laboratory chimpanzees. Males experienced lower dysregulation in both contexts, and the two populations exhibited distinct aging patterns based on the body system. Our results support the conclusion that naturalistic living conditions result in healthier aging in chimpanzees. These data provide support for the proposal that lifestyle effects on human health and aging are conserved from deeper into our evolutionary history.</p>
Fig. 3 in Skin Microbiome Of Free-Living European Pond Turtle (Emys Orbicularis (L.)) On The Northern Border Of Its Range In Silene Nature Park, Latvia
Fig. 3. Gram-positive (A) and Gram-negative bacteria (B) under the microscope. Magnification x1000.
Fig. 2 in Skin Microbiome Of Free-Living European Pond Turtle (Emys Orbicularis (L.)) On The Northern Border Of Its Range In Silene Nature Park, Latvia
Fig. 2. Sampled turtle with the biotope (Photo: M. Pupins).
Fig. 1 in M Or P Ho L O Gi Ca L Va R Iati On An D P Op U Lat Io N Structure Of The Natterjack Toad, Epidalea Calamita, In Northern Part Of The Range In Belarus
Fig. 1. Natterjack toad Epidalea calamita in Belarus.
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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.
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