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5,990 results for “reproduction”
Maple Reproduction and Sap Flow at Harvard Forest since 2011
Seed production assures the persistence of tree populations and forest cover over the long-term, and so has long interested plant demographers and foresters. Many forest tree species produce seeds synchronously and at irregular intervals across large areas, a phenomenon known as masting. Initiated in spring 2011, this study addresses the mechanisms of mast seeding in sugar maple (Acer saccharum), and its impact on pollinators, seed consumers, and forest carbon dynamics at the Harvard Forest. We monitor seed production (via counts of seeds on trees), flower production, and resource status (via sap collection) on 20 trees. Pollinator dynamics and seed predation (by weevils) are also monitored. In 2015, we added sap and seed monitoring of red maple (Acer rubrum) trees to explore the hypothesis that this non-masting species would have muted dynamics compared to its masting congener.
Evaluation of Mask R-CNN Model for Counting Reproductive Structures of Six Plant Species 1895-2018
Phenology––the timing of life-history events––is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current common practice of manually harvesting data from individual specimens greatly restricts our ability to scale data collection to entire collections. Recent investigations have demonstrated that machine-learning models can facilitate data collection from herbarium specimens. However, present attempts have focused largely on simplistic binary coding of reproductive phenology (e.g., flowering or not). Here, we use crowd-sourced phenological data of numbers of buds, flowers, and fruits of more than 3000 specimens of six common wildflower species of the eastern United States (Anemone canadensis, A. hepatica, A. quinquefolia, Trillium erectum, T. grandiflorum, and T. undulatum} to train a model using Mask R-CNN to segment and count phenological features. A single global model was able to automate the binary coding of reproductive stage with greater than 90% accuracy. Segmenting and counting features were also successful, but accuracy varied with phenological stage and taxon. Counting buds was significantly more accurate than flowers or fruits. Moreover, botanical experts provided more reliable data than either crowd-sourcers or our Mask R-CNN model, highlighting the importance of high-quality human training data. Finally, we also demonstrated the transferability of our model to automated phenophase detection and counting of the three Trillium species, which have large and conspicuously-shaped reproductive organs. These results highlight the promise of our two-phase crowd-sourcing and machine-learning pipeline to segment and count reproductive features of herbarium specimens, providing high-quality data with which to study responses of plants to ongoing climatic change.
Visual Counts of Tree Reproduction near NEON plots at Harvard Forest since 2020
Mast seeding, a resource pulse that has cascading effects in the environment, is a measure that can provide insight into forest dynamics. When masting data is collected in sequential years it can provide information on how tree populations are responding to climatic and environmental variables, and can also be used to relate to other indices, such as seed-eating animal species. The objective of this study is to quantify the yearly seed production of mast seeding tree species at Harvard Forest which are located near National Ecological Observatory Network (NEON) plots. This project is part of larger NEON-enabled project examining mast seeding on a continental scale at 25 NEON sites in the United States, which uses mast seeding records in conjunction with NEON collected data products like mammal box-trapping, tick drags, and bird point counts. Data collected on mast seeding can be linked to these other indices at regional and continental scales.
PRE02 Reproductive effort of Big Bluestem, Indiangrass and Little Bluestem on selected Konza Prairie LTER watersheds
This data set focuses on seed production, flowering stem mass, height, and population densities of three dominant prairie grasses: Andropogon gerardii (ANGE), Sorgastrum nutans (SONU), and Schizachyrium scoparium (ANSC) in selected Konza Prairie LTER watersheds. Data set includes measurements of flowering stem height (m), density (no. per sq. m) and production (grams per sq. m) and total seed weight (grams) and production (grams per sq. on 2 soil types (shallow and deep) in watersheds representing different burning-grazing treatment combinations. Specific watersheds sampled have varied over time. Current watersheds include: 001d, R01a, R01b, 002c, 002d, 004a, 004b, 020b, R20a, R20b, 0SpA, 0SpB, 0SuA, 0SuB, 00FA, 00FB, 00WA and 00WB Sampling is done once a year in October/November (end of growing season). (Sampling design slightly altered from PRE01).
Individual plant growth and reproduction in the black sand extended growing season experiment for East Knoll, Audubon, Lefty, and Trough sites, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes measurements of growth and reproduction for Geum plants as well as counts of buds and flowers were counted and recorded for each tagged study plant, within all snow and warming treatments at all sites except Soddie.
Data and code for: Rachel A Reeb, J Mason Heberling, & Sara E Kuebbing (2024). Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity. AoB PLANTS, plae058
<p>Data and Analysis Code for: </p> <p>Rachel A Reeb, J Mason Heberling, Sara E Kuebbing (2024). Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity. <em>AoB PLANTS</em>, plae058. <a href="https://doi.org/10.1093/aobpla/plae058">https://doi.org/10.1093/aobpla/plae058</a></p> <p>Includes two R markdown files ("climate_data_extraction_code.rmd" is the script for data extraction and cleaning and "Data_Analysis_V2.rmd" is the analysis script), the associated datasets (in .csv format), and the metadata file ("readme.txt").</p>
Replication package of "Search-based Crash Reproduction using Behavioral Model Seeding"
<p>Search-based crash reproduction approaches assist developers during debugging by generating a test case which reproduces a crash given its stack trace. One of the fundamental steps of this approach is creating objects needed to trigger the crash. One way to overcome this limitation is seeding: using information about the application during the search process. With seeding, the existing usages of classes can be used in the<br> search process to produce realistic sequences of method calls which create the required objects. In this study, we introduce behavioral model seeding: a new seeding method which learns class usages from both<br> the system under test and existing test cases. Learned usages are then synthesized in a behavioral model (state machine). Then, this model serves to guide the evolutionary process. To assess behavioral model-seeding, we evaluate it against test-seeding (the state-of-the-art technique for seeding realistic objects) and no-seeding (without seeding any class usage). For this evaluation, we use a benchmark of 122 hard-to-reproduce crashes stemming from six open-source projects. Our results indicate that behavioral model-seeding outperforms both test seeding and no-seeding by a minimum of 6% without any notable negative impact on efficiency.</p>
Data from 'Tracability of Forest Reproductive Material with the quality label 'Plant van Hier': A DNA database with genetic profiles of native autochthonous tree and shrub species of Flanders, Belgium'
<h2>Background</h2> <p>Indigenous trees and shrubs play an important role in multifunctional forest management. They form a significant part of the biodiversity in our forests. Forest reproductive material (FRM) of autochthonous Flemish origin is sold under the quality label ‘Plant van Hier’, a certification mark of the Agency for Nature and Forests. To ensure the provenance of the seedlings, we developed a DNA-database of genetic profiles of potential parent trees, using species-specific genetic markers. This database enables the traceability of FRM of the ‘Plant van Hier’ label throughout the entire production chain; from seed harvesting and cultivation to planting by the end user.</p> <p>This database contains the genetic profiles of almost all possible parent trees present within 27 Flemish autochthonous seed orchards of eight ecologically important tree and shrub species: <em>Carpinus betulus</em>, <em>Corylus avellana</em>, <em>Frangula alnus</em>, <em>Populus tremula</em>, <em>Sorbus aucuparia</em>, <em>Tilia cordata</em>, <em>Tilia platyphyllos,</em> and <em>Ulmus laevis</em>. The profiles were established using microsatellite markers (11 to 24 markers per species). New genetic markers were developed for <em>Carpinus betulus</em> and <em>Ulmus laevis</em>. PCR products were run on an ABI 3500 Genetic Analyser (Thermo Fisher Scientific).</p> <h2>Files</h2> <p>The files will be updated when new genotypes are added to the seed orchards. The current data files contain data from genotypes collected in the period 2018-2023. </p> <h3>Species_genotypes</h3> <p>These files contain the genetic fingerprints of the parent trees of autochthonous Flemish seed orchards. Missing data is indicated as ‘MD’. For <em>Carpinus betulus</em>, an octoploid species, the allelic phenotype is given instead of the genotype as the number of times that an allele occurs on a specific locus is not known.</p> <p>The next metadata is additionally given:<br>- Species: the Latin name of the species<br>- Seed_orchard: the name of the seed orchard in which the genotypes are located<br>- Code_seed_orchard: the code of the seed orchard in which the genotypes are located as given in the Register of Flemish Forest Reproductive Material (‘Register bosbouwkundig uitgangsmateriaal’; inbo.be)<br>- Genotype: the fieldname given to the genotype<br>- Origin: the location where the genotype was collected in Flanders, Belgium. Genotypes were collected from natural stands which are assumed to have an autochthonous origin. When the specific location is unknown, the location ‘Flanders’ is given. <br>- Year_sampled: the year in which the genotypes were sampled in the respective seed orchard for genetic analysis.</p> <h3>Species_binsets</h3> <p>These files contain the binsets and allele names that are used to score the alleles of the genotypes in the programme Geneious Prime 2019.3.2 (<a href="https://www.geneious.com">https://www.geneious.com</a>). For <em>Tilia platyphyllos </em>and <em>Tilia cordata</em>, the same binsets were used.</p>
Reproduction package for the paper "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"
<p>Research Data Management package for "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"</p> <p>Authors: Sam Geen & Alex de Koter</p> <p>Status: Accepted by MNRAS<br> This package aims to provide a full data reproduction pipeline. Please see Readme.md for more information.</p>
MUSE HUDF survey I, Section 4: data and reproduction pipeline for photometry and astrometry
<p>Necessary data and <a href="http://akhlaghi.org/reproducible-science.html">Reproduction pipeline</a> for <a href="https://www.aanda.org/articles/aa/full_html/2017/12/aa30833-17/aa30833-17.html#S14">Section 4</a> of "<em>The MUSE Hubble Ultra Deep Field Survey: I. Survey description, data reduction and source detection</em>", Bacon et al. (2017), <a href="https://www.aanda.org/articles/aa/abs/2017/12/aa30833-17/aa30833-17.html">Astronomy & Astrophysics, 608, A1</a>. The purpose of this section in the paper is to show the photometric and astrometric precision of the processed <a href="http://muse-vlt.eu/science/">MUSE</a> 3D data cubes discussed in the paper (pseudo-broad-band images created from the cubes) in comparison with broad-band images of the Hubble Space Telescope (HST).</p> <p>This repository on Zenodo contains all the necessary input data, software and <a href="http://akhlaghi.org/reproducible-science.html">reproduction pipeline</a> (containing the scripts, configuration files and settings to exactly reproduce the results in Section 4 of the paper). Below is a description of the contents:</p> <ul> <li> <p><a href="https://zenodo.org/record/1163746/files/gnuastro-0.2.51-bc56.tar.gz"><code>gnuastro-0.2.51-bc56.tar.gz</code></a>: The version of <a href="https://www.gnu.org/software/gnuastro">GNU Astronomy Utilities</a> (Gnuastro) that is necessary for this pipeline. Gnuastro is a large collection of programs for astronomical data analysis on the command-line (and in scripts). Note that the reproduction pipeline <em>only</em> works with Gnuastro version 0.2.51, it will complain and abort if another version is installed.</p> <p>IMPORTANT NOTE: Since version 0.2.51 of Gnuastro was released, CFITSIO (one of Gnuastro's dependencies) has added a dependency for the cURL library (to read https URLs). Therefore, to install Gnuastro 0.2.51, please install <a href="https://heasarc.gsfc.nasa.gov/FTP/software/fitsio/c/cfitsio3410.tar.gz">CFITSIO version 3.41</a> or earlier.</p> </li> <li> <p><a href="https://zenodo.org/record/1163746/files/gnuastro-dependencies.tar.gz"><code>gnuastro-dependencies.tar.gz</code></a>: Software libraries necessary to build Gnuastro as it is used here. With these, a working C compiler is enough (currently only tested in a GNU/Linux environment) to exactly reproduce the results (tables).</p> </li> <li> <p><a href="https://zenodo.org/record/1163746/files/hst-acs-images.tar.gz"><code>hst-acs-images.tar.gz</code></a>: Necessary images from HST's <a href="https://archive.stsci.edu/prepds/xdf/">eXtreme Deep Field</a> survey <a href="https://archive.stsci.edu/pub/hlsp/xdf">archives</a>. These images are not necessary to run the reproduction pipeline (they will be downloaded from the HST archives if not present). They are stored here for the self-sufficiency of this repository and faster download: in this lossless compressed format, they are roughly 1/3rd the volume of the same files in HST archives.</p> </li> <li> <p><a href="https://zenodo.org/record/1163746/files/hst-acs-throughputs.tar.gz"><code>hst-acs-throughputs.tar.gz</code></a>: The throughputs of HST Advanced Camera for Surveys (ACS) filters necessary in this study. These are also available from the <a href="http://www.stsci.edu/hst/acs/analysis/throughputs/tables">HST archives</a> and are kept here with similar reasons to above.</p> </li> <li> <p><a href="https://zenodo.org/record/1163746/files/muse-pseudo-broadband-images.tar.gz"><code>muse-pseudo-broadband-images.tar.gz</code></a>: Pseudo-broad-band images generated from the MUSE 3D data cube. These images are only released in this repository. However, to run the reproduction pipeline, it isn't necessary to download them directly from here. The script will download them from Zenodo automatically.</p> </li> <li> <p><a href="https://zenodo.org/record/1163746/files/reproduce-v1-4-gaafdb04.tar.gz"><code>reproduce-v1-4-gaafdb04.tar.gz</code></a>: The <a href="http://akhlaghi.org/reproducible-science.html">reproduction pipeline</a> (version 1-4-gaafdb04) that produces the results (tables) plotted in the paper. The full Git version controlled history of this repository is available on <a href="https://git-cral.univ-lyon1.fr/mohammad.akhlaghi/muse-udf-photometry-astrometry">git-cral.univ-lyon1.fr</a> or <a href="https://gitlab.com/makhlaghi/muse-udf-photometry-astrometry">gitlab.com</a>. We recommend cloning from the Git repository if it is available. This tarball is kept here in case those servers don't work or Git is no longer in common use. Please see the <code>README</code> file in this repository for instructions on how to run the reproduction pipeline and exactly reproduce the results. This pipeline will download all the necessary data if they aren't already present on the system (it is probably just necessary to install the required version of Gnuastro).</p> </li> </ul> <p>The Creative Commons Attribution-NonCommercial 4.0 copyright mentioned in the Zenodo webpage is only applicable to files that don't have an explicit copyright within them. The copyright of other files (mainly scripts and software) is mentioned within them (all are <a href="https://www.gnu.org/licenses/licenses.en.html">free licenses</a>).</p> <p>For any issues with the pipeline/processing, please contact <a href="http://akhlaghi.org">Mohammad Akhlaghi</a>.</p>
Data from: Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide
<p><strong>Summary</strong></p> <p>This dataset accompanies the publication "<strong>Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide</strong>" published in Zoo Biology. It contains anonymised data from 540 captive flamingo populations, and includes the four species: <em>Phoeniconaias minor, Phoenicopterus chilensis, Phoenicopterus roseus</em> and<em> Phoenicopterus ruber</em>. Data were sourced from the Zoological Information Management System (ZIMS), operated by Species360 (https://www.species360.org/). ZIMS is the largest real-time database of comprehensive and standardized information spanning more than 1,200 zoological collections globally, and provides the number of institutions currently managing each flamingo species and both their current and historic population sizes. These data were used to investigate the relationship between reproductive success and both flock size, and structure, on a global scale.</p> <p>This dataset also contains climatic data provided by WorldClim, which were used to assess the influence of climatic variables on captive flamingo reproductive success globally. The WorldClim database averages 19 different climatic variables derived from monthly temperature and rainfall values at a 1 km spatial resolution for the period 1970-2000. Using geographic coordinates (latitude and longitude) we calculated several climatic metrics for each institution. </p> <p> </p> <p><strong>Description of the Dataset</strong></p> <p>One file is provided for each species (<em>P. minor, P. chilensis, P. roseus </em>and <em>P. ruber</em>) as a csv file. Each file contains the following 15 columns:</p> <ul> <li><strong>Institution Code: </strong>An anonymous code used to identify individual zoological institutions. </li> <li><strong>Country: </strong>The country where the institution is located.</li> <li><strong>Year: </strong>Current year (<em>t</em>).</li> <li><strong>Flock Size:</strong> Flock size in year <em>t.</em></li> <li><strong>Males: </strong>The number of males in the flock in year <em>t.</em> </li> <li><strong>Females:</strong> The number of females in the flock in year <em>t.</em></li> <li><strong>Unsexed:</strong> The number of unsexed individuals in the flock in year <em>t.</em></li> <li><strong>Proportion of Females: </strong>The proportion of the flock made up of female individuals in year <em>t</em>. </li> <li><strong>Proportion of Unsexed:</strong> The proportion of the flock made up of unsexed individuals in year <em>t.</em></li> <li><strong>Hatches:</strong> Number of birds hatched in year <em>t.</em></li> <li><strong>Proportion of Additions:</strong> The proportion of the flock in year <em>t</em> made up of additions from year <em>t-1</em> (not including new birds hatched into the flock).</li> <li><strong>MAP: </strong>Mean annual precipitation (mm).</li> <li><strong>MAT: </strong>Mean annual temperature (°C).</li> <li><strong>MAP Var: </strong>Mean annual variation in precipitation (MAP coefficient of variation).</li> <li><strong>MAT Var: </strong>Mean annual variation in temperature (MAT standard deviation).</li> </ul> <p>Note: Mean Annual Temperature (MAT) is provided by WorldClim as °C multiplied by 10, and similarly mean annual variation in temperature as MAT standard deviation multiplied by 100. In the corresponding publication, both were divided (by 10 and 100 respectively) prior to modelling to avoid confusion in the units used.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We acknowledge and thank all Species360 member institutions for their continued support and data input. The research which data refers to was funded by the Irish Research Council Laureate Awards 2017/2018 IRCLA/2017/60 to Y.M.B. Additionally, S.Q.S. received funding from the International Max Planck Research School for Organismal Biology. The Species360 Conservation Science Alliance would like to thank their sponsors: the World Association of Zoos and Aquariums, Wildlife Reserves of Singapore, and Copenhagen Zoo. </p> <p> </p> <p><strong>Disclaimer</strong></p> <p>Despite our best efforts at screening the data for errors and inconsistencies, some information could be erroneous. Similarly, data contained within ZIMS are based on submitted records from individual institutions, and are not subject to editorial verification, potentially permitting errors or failure to update species holdings etc. Despite this, ZIMS represents the only global database of zoo collection composition records, and as a result, is used by the IUCN, Convention on International Trade in Endangered Species (CITES), the Wildlife Trade Monitoring Network (TRAFFIC), United States Fish and Wildlife Service (USFWS) and Department for Environment, Food and Rural Affairs (DEFRA). </p> <p> </p> <p><strong>Credit</strong></p> <p>If you use this dataset, please cite the corresponding publication:</p> <p>Mooney, A., Teare, J. A., Staerk, J.,Smeele, S. Q., Rose, P., Edell, R. H., King, C. E., Conrad, L., & Buckley, Y. M. (2023). Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide.<em> Zoo Biology</em>, 1–14. <a href="https://doi.org/10.1002/zoo.21753">https://doi.org/10.1002/zoo.21753</a></p> <p> </p> <p> </p>
Native tree growth and reproduction in response to reduction in the coconut palm (Cocos nucifera) canopy at Palmyra Atoll
These data describe competition for light (open solar path) between introduced coconut palm trees (Cocos nucifera) and native tree species between 2004 and 2008 at Palmyra Atoll, Northern Line Islands, Pacific Ocean. Data are contained in one table, including values from the start, end, and intermediate samples. The dataset measures the change in tree growth (DBH and height) and reproductive potential (flower and fruit production) in relation to time and open solar path value. Two treatments are considered: OSP values less than 50% created by C. nucifera removal, and OSP values greater than 50%.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Plant Reproductive Success
These data describe annual estimates reproductive success (measured by seed set) of salt marsh plants at the San Dieguito Wetland as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to track long-term patterns in reproductive success of wetland plants. Monitoring began in 2012.
Geographical variation in vegetative growth and sexual reproduction of the invasive Spartina alterniflora in China
We studied patterns in vegetative growth and sexual reproduction of introduced S. alterniflora at 22 sites at 11 geographic locations over a latitudinal gradient of ~2000 km from Tanggu (39.05 °N, high latitude) to Leizhou (20.90 °N, low latitude) in China. We further evaluated the basis of phenotypic differences by growing plants from across the range in a common garden for 2 growing seasons. We found distinct latitudinal clines in plant height, shoot density, and sexual reproduction across latitude. Some traits exhibited linear relationships with latitude; others exhibited hump-shaped relationships. We identified correlations between plant traits and abiotic conditions such as mean annual temperature, growing degree days, tidal range, and soil nitrogen content. However, geographic variation in all but one trait disappeared in the common garden, indicating that variation largely due to phenotypic plasticity. Only a slight tendency for latitudinal variation in seed set persisted for two years in the common garden, suggesting that plants may be evolving genetic clines for this trait. Note that these data were collected as part of a National Natural Science Foundation of China (NSFC) funded study led by Yihui Zhang in collaboration with GCE-LTER.
CBS03 Grasshopper sparrow surveys: densities, reproductive index, and locations of marked individuals on Konza Prairie
Data on the location, identity, and reproductive index (Vickery et al. 1992) of Grasshopper Sparrows prior to 2017, and after that, additionally many Dickcissels, Eastern Meadowlarks, Brown-headed Cowbirds and other songbirds within 10-ha plots on multiple watersheds units on Konza and on two adjoining units on the Rannells Preserve. Each plot was surveyed every ~7-10 days. These surveys documented individual sparrow, Dickcissel, and Eastern Meadowlark locations, and are used to calculate dispersal distances and territory densities and movements. Missing values in character fields denoted by NA, and in numeric fields, either -999 or -9.
PBG04 Reproductive effort of Big Bluestem, Indiangrass and Little Bluestem in the Patch-Burn Grazing Experiment at Konza Prairie
'PBG' datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. PBG041 includes data on flowering stem height (m) of three dominant prairie grasses: Andropogon gerardii (ANGE), Sorghastrum nutans (SONU), and Schizachyrium scoparium (ANSC). PBG042 includes flowering stem density (no. per sq. m) and mass (grams per sq. m) for the same grass species.
PFS01 Reproductive effort of Big Bluestem, Indiangrass, and Little Bluestem on belowground plots
Data collected to assess the effects of burning, mowing and fertilizer treatments in the Belowground Plot Experiment upon flowering stem height and density of big bluestem (Andropogon gerardii), little bluestem (A. scoparious) and Indian grass (Sorghastrum nutans), and total aboveground net primary productivity.
Adelie penguin reproduction success, 1991-2024
The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Two hypotheses have guided this research, with one suggesting that population mean fitness is best explained by changes in regional krill biomass, and the other proposing that long-term changes in sea ice affects mean fitness by tipping the balance in favor of one species over another in accordance with species-specific evolved life history affinities to sea ice. Although these hypotheses are not mutually exclusive, current evidence in the PAL region tends to favor the latter over the former. Since the inception of PAL, Adélie penguin populations have effectively collapsed, while those of gentoo and chinstrap penguins have increased dramatically, trends that are spatially and temporally coherent with decreasing regional sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. In contrast, although krill constitute the most important component of the summer diets by mass of these three penguin species, changes in PAL krill abundances have exhibited no long-term trends, and thus fail to explain the divergent patterns in penguin populations evident in our time series. No lay dates were recorded during the 2020-2021 season due to a late start to the field season due to COVID. No data collected during the 2021-2022 season due to the Palmer Station Pier Build.
Replication package of "Good Things Come In Threes: Improving Search-based Crash Reproduction With Helper Objectives"
<p>The replication package for the study about using new helper objectives (MOHO) for crash reproduction. This study has been accepted at ASE 2020.</p> <p> </p> <p>Abstract:</p> <p>Evolutionary intelligence approaches have been successfully applied to assist developers during debugging by generating a test case reproducing reported crashes. These approaches use a single fitness function called <em>Crash Distance</em> to guide the search process toward reproducing a target crash. Despite the reported achievements, these approaches do not always successfully reproduce some crashes due to a lack of test diversity (premature convergence). In this study, we introduce a new approach, called <em>MO-HO</em>, that addresses this issue via multi-objectivization. In particular, we introduce two new Helper-Objectives for crash reproduction, namely <em>test length</em> (to minimize) and <em>method sequence diversity</em> (to maximize), in addition to <em>Crash Distance</em>.</p> <p>We assessed <em>MO-HO</em> using five multi-objective evolutionary algorithms (NSGA-II, SPEA2, PESA-II, MOEA/D, FEMO) on 124 hard-to-reproduce crashes stemming from open-source projects. Our results indicate that SPEA2 is the best-performing multi-objective algorithm for <em>MO-HO</em>.</p> <p>We evaluated this best-performing algorithm for <em>MO-HO</em> against the state-of-the-art: single-objective approach (Single-Objective Search) and decomposition-based multi-objectivization approach (<em>De-MO</em>). Our results show that <em>MO-HO</em> reproduces five crashes that cannot be reproduced by the current state-of-the-art. Besides, <em>MO-HO</em> improves the effectiveness (+10% and +8% in reproduction ratio) and the efficiency in 34.6% and 36% of crashes (i.e., significantly lower running time) compared to Single-Objective Search and <em>De-MO</em>, respectively. For some crashes, the improvements are very large, being up to +93.3% for reproduction ratio and -92% for the required running time. </p>
Phenotype data for Sussex LHM Drosophila melanogaster reproductive fitness GWAS
<p>Input data, code, logs, graphs and output data for the Sussex LHM Drosophila melanogaster hemiclones.</p> <p>Aim is to generate single, standardised values of female and male reproductive fitness for each hemiclone genome, for using in genome-wide association test using Plink software.</p> <p>Notes on how to run are provided in the code.</p>
ScienceDex guides
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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.