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3,100 results for “Recent”
LANDIS-II PnET Simulation of Recent Trends in Forest Change in New England 2010-2060
The future forests of eastern North America will be shaped by at least three broad drivers: (i) vegetation change and natural disturbance patterns associated with the protracted recovery following colonial era land use, (ii) a changing climate, and (iii) a land-use regime that consists of geographically variable rates and intensities of forest harvesting, clearing for development, and land protection. We evaluated the aggregate and relative importance of these factors for the future forests of New England, USA by simulating a continuation of the recent trends in these drivers for fifty-years, nominally spanning 2010 to 2060. The models explicitly incorporate the modern distribution of tree species and the geographical variation in climate and land-use change. Using a cellular land-cover change model in combination with a physiologically-based forest landscape model, we conducted a factorial simulation experiment to assess changes in aboveground carbon (AGC) and forest composition. In the control scenario that simulates a hypothetical absence of any future land use or future climate change, the simulated landscape experienced large increases in average AGC—an increase of 53% from 2010 to 2060 (from 4.2 to 6.3 kg m-2). By 2060, climate change increased AGC stores by 8% relative to the control while the land-use regime reduced AGC by 16%. Among land uses, timber harvesting had a larger effect on AGC storage and changes in tree composition than did forest conversion to non-forest uses, with the most pronounced impacts observed on private corporate-owned land in northern New England. Our results demonstrate a large difference between the landscape’s potential to store carbon and the landscape’s current trajectory, assuming a continuation of the modern land-use regime. They also reveal aspects of the land-use regime that will have a disproportionate impact on the ability of the landscape to store carbon in the future, such as harvest regimes on corporate-owned lands. This
Forest structural diversity at NEON sites in the continuous USA that experienced recent moderate disturbance
Disturbances can change the structural diversity of forests through time, which can be measured from three-dimensional data provided by LiDAR. Discrete-return LiDAR was used to measure a suite of 19 structural diversity metrics that describe the height, cover and openness, vegetation density, and internal and external heterogeneity of forest vegetation at NEON base plots. Discrete-return LiDAR point clouds from the NEON Aerial Observation Platform (DP1.30003.001) were downloaded September of 2020 and used to estimate the metrics within 40 x 40 m base plots. Metrics were estimated from base plots at 15 NEON forested sites from provisional LiDAR data available from 2014 to 2020. The workflow that produced the data was developed in the program R.
Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation
<div> <div> <p>The dataset accompanying the manuscript titled "Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation" provides comprehensive information on streamflow patterns in the Colorado River since 2000. The dataset is needed to run the analysis available on GitHub available <a href="https://github.com/dlhogan97/Spring-Precipitation-Effect-CO-River.git">here</a>. This is version 2, please use this version for the most up-to-date results.</p> <p><strong>Please read the accompanying README (available in the README.md file) for individual file descriptions and file nesting strategy that should be employed to easily reproduce this analysis.</strong></p> <p>The dataset covers a range of variables related to streamflow and precipitation, including but not limited to discharge measurements, seasonal variations, and relevant meteorological data. The primary focus of the dataset is to elucidate the observed streamflow deficits in the Colorado River, attributing these changes to decreased spring precipitation.</p> <p>Key features of the dataset include:</p> <ul> <li> <p>Time Coverage: The dataset spans a specified time range that aligns with the investigation into recent streamflow deficits in the Colorado River between 1964 and 2022.</p> </li> <li> <p>Spatial Scope: It includes data from relevant monitoring stations along within the Upper Colorado River, but focusing in the hydrologically vital headwater regions, providing a spatially distributed perspective.</p> </li> <li> <p>Variables: The dataset encompasses a variety of variables essential for understanding streamflow dynamics, with a particular emphasis on the impact of reduced spring precipitation.</p> </li> </ul> <p>Researchers and stakeholders interested in hydrological patterns, climate-driven changes, and water resource management in the Colorado River Basin will find this dataset valuable. It serves as a foundational resource for reproducibility, further analysis, and collaboration within the scientific community. The dataset is deposited on Zenodo to facilitate open access, sharing, and citation for broader research endeavors.</p> </div> </div>
FraneItalia: a catalog of recent Italian landslides
<p><strong>FraneItalia</strong> is a geo-referenced catalog of recent landslides affecting the Italian territory. The catalog has been <strong>developed consulting online news sources from 2010 </strong><strong>onward</strong> and it includes both fatal landslide events and events that did not produce physical harm to people. Landslide events are classified considering two numerosity categories and three consequence categories.</p> <p>NUMEROSITY CATEGORIES</p> <ul> <li><strong>Single Landslide Events</strong> (<strong>SLE</strong>), for records only reporting one landslide;</li> <li><strong>Areal Landslide Events</strong> (<strong>ALE</strong>), for records referring to multiple landslides triggered by the same cause in the same geographic area.</li> </ul> <p>Note: the ALE category has been introduced to simplify collection of the landslide records for the numerous cases when many landslides are mentioned together in the news.</p> <p>CONSEQUENCE CATEGORIES</p> <ul> <li><strong>Very severe consequences</strong> (<strong>C1</strong>), for events with victims and/or missing people;</li> <li><strong>Severe consequences</strong> (<strong>C2</strong>), for events with injured persons and/or evacuations;</li> <li><strong>Minor consequences</strong> (<strong>C3</strong>), for events that did not cause physical harm to people.</li> </ul> <p>Note: the consequence classification is based on the severity of the effects to human life not considering other consequence measures (e.g., economic loss, environmental damage)</p> <p>INFORMATION on each recorded landslide event includes:</p> <ul> <li>data on the location of the event [compulsory entries]</li> <li>day of occurrence of the landslide(s) [compulsory entry]</li> <li>duration of the landslide event [if applicable]</li> <li>number of landslides for ALE [compulsory entry]</li> <li>classes of accuracy of the spatial and temporal data [compulsory entries]</li> <li>source(s) of information [compulsory entries]</li> <li>landslide characteristics [optional entries]</li> <li>phase of activity [optional entry]</li> <li>details on the consequences [optional entries]</li> </ul>
Model data for "Recent irreversible retreat phase of Pine Island Glacier"
<p>Model inputs and outputs for the experiments in Reed et al., 2023 "Recent irreversible retreat phase of Pine Island Glacier".</p>
Tree diameter growth and increment core δ13C data from a recently thinned forestry-drained site (Lettosuo) in southern Finland.
<p>Dataset includes increment core data from Lettosuo drained peatland forest site. The study site locates in the Tammela municipality in southern Finland (60° 38’ 31’’ N, 23° 57’ 35’’ E). Increment cores were analysed for the ring widths for dominant and suppressed Norway spruce trees, and for the ring δ<sup>13</sup>C values from suppressed Norway spruce trees. Data was collected as a part of BiBiFe (”Biogeochemical and biophysical feedbacks from forest harvesting to climate change”) consortium that is funded by the Academy of Finland. </p> <p> </p> <p>Sampling for increment cores was done during October 2020 for sample trees (10 in total, of which 5 were suppressed trees from thinned area and 5 suppressed trees from control area) and additional sampling was conducted for annual diameter increment for 3 tree groups to increase sample size for diameter growth (suppressed trees in thinned area [n=20], dominant trees in thinned area [n=22] and suppressed trees in control area[n=20]) during March 2021. </p> <p> </p> <p><strong>Tree </strong><strong>ring carbon isotope data</strong></p> <p> </p> <p>Laser ablation IRMS method was applied in the Stable Isotope Laboratory of Luke (SILL) to quantify δ<sup>13</sup>C values in 10 increment cores for the time period 2010–2020, following principles of Schulze et al. (2004) and described in Lehtonen et al (manuscript). Up to 11 evenly spaced “spots” for each annual tree ring were measured to obtain information on the intra-annual variation of δ<sup>13</sup>C of the samples. </p> <p> </p> <p>(1) File: Lettosuo_d13C.xls</p> <p>File includes d13C measurements</p> <p> </p> <p><strong>Data column description below for isotope data: </strong></p> <p> </p> <p><strong>id</strong> stands for tree id [id includes tree identity, year and also spot number]</p> <p><strong>year</strong> is the year of the tree ring</p> <p><strong>nr</strong> is an index for data </p> <p><strong>tree</strong> indicates tree identity "C" for control and "H" for harvest</p> <p><strong>treatment</strong> indicates the treatment of the sampling area (control / harvest)</p> <p><strong>d13C</strong> gives the measured d13C value based on the LA-IRMS measurements</p> <p><strong>season </strong>indicates whether observation originated from the earlywood (EW) or latewood (LW) period, where 1 is EW and 2 is LW</p> <p> </p> <p><strong>Tree ring width measurements</strong></p> <p> </p> <p>In addition to the δ<sup>13</sup>C values, also the ring widths were measured. Here, also additional dominant trees were measured. </p> <p> </p> <p>(3) Files:</p> <p>controlRW.csv</p> <p>dominantRW.csv</p> <p>thinningRW.csv</p> <p> </p> <p>Files include increment core data (in micrometers) from isotope sample trees and additional increment core trees from the control area and harvested area of the site. Dominant trees were measured only from the thinned area. </p> <p> </p> <p>In the .csv files individual columns are for ring widths for individual trees. In the controlRW.csv and thinningRW.csv files first 5 columns include diameter increments from sample trees (those that have also d13C measurements).</p> <p> </p> <p><strong>References:</strong></p> <p> </p> <p>Lehtonen A, Leppä K, Sahlstedt E, Schiestl-Aalto P, Heikkinen J, Young G, Korkiakoski M, Peltoniemi M, Rinne-Garmston K, Sarkkola S, Lohila A, Mäkipää R (manuscript). Fast recovery of Norway spruce trees after thinning from above on a drained peatland forest site.</p> <p> </p> <p>Korkiakoski M, Ojanen P, Penttilä T, Minkkinen K, Sarkkola S, Rainne J, Laurila T, Lohila A (2020) Impact of partial harvest on CH<sub>4</sub> and N<sub>2</sub>O balances of a drained boreal peatland forest. Agric For Meteorol 295:108168.</p> <p> </p> <p>Schulze B, Wirth C, Linke P, Brand WA, Kuhlmann I, Horna V, Schulze E-D (2004) Laser ablation-combustion-GC-IRMS--a new method for online analysis of intra-annual variation of 13C in tree rings. Tree Physiol 24:1193–1201.</p>
Data used in: 'Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 1: Stratospheric chlorine budget and the role of transport' by Bednarz et al. (2022)
<p>Data used in: 'Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 1: Stratospheric chlorine budget and the role of transport' by Bednarz et al. (2022), which has been accepted for publication in Atmospheric Chemistry and Physics.</p> <p> </p>
Comparing recent PTA results on the nanohertz stochastic gravitational wave background - full noise and GWB parameter comparison plots
<p>A full collection of plots comparing the noise properties of individual pulsars and gravitational wave background parameters discussed in the companion paper <em>Comparing recent PTA results on the nanohertz stochastic gravitational wave background</em> (IPTA 2024).</p> <p><code>Section4_GWB_comparison.zip</code> supplements and expands section 4.1, "Comparing the published GWB measurements," of IPTA (2024). It contains parameter difference distributions for GWB model parameters. There are four different models included. The HD correlated powerlaw (PL) model make up the basis for Figure 2. Additionally, there are three comparisons not included in IPTA (2024). First, comparisons the common uncorrelated red noise (CURN) PL model are included. Finally, comparisons of two free spectral (FS) models (HD and CURN) are included. These comparisons fit the HD and CURN FS posteriors using the <code>ceffyl</code> software package, and then compare the parameters of the resulting powerlaw fits.</p> <p><code>Section5_Noise_comparison.zip</code> supplements section 5, "Comparing Pulsar Noice Properties," of IPTA (2024). It contains plots for 27 pulsars timed by more than one PTA collaboration, including the plots for PSR J1012+5307, which are presented in Figure 7. The plots include noise parameter posteriors, time domain GP realizations, TOA residuals, and TOA radio frequency.</p>
Bibliometric Analysis on Recent Topics in ILS Research
<p><strong><span>Bibliometric Analysis on Recent Topics in ILS Research</span></strong></p> <p><span><span> </span></span></p> <p><span>Pablo Rosser (Corresponding Author)<span> </span></span></p> <p><span>Faculty of Education, International University of La Rioja, Spain<span> </span></span></p> <p><span>Avenida de la Paz 137, 26006 Logroño, La Rioja, Spain - pablo.rosser@unir.net<span> </span></span></p> <p><span>Phone: +34 607321642<span> </span></span></p> <p><span>ORCID: 0000-0002-9802-7169</span></p> <p><span><br><br></span></p> <p><span>Seila Soler<span> </span></span></p> <p><span>Faculty of Humanities and Social Sciences, Isabel I University, Spain<span> </span></span></p> <p><span>C. de Fernán González 76, 09003 Burgos, Spain<span> </span></span></p> <p><span>seilaaixa.soler@ui1.es<span> </span></span></p> <p><span>Phone: +34 687704604<span> </span></span></p> <p><span>ORCID: 0009-0001-9125-3382</span></p> <p><span><span> </span></span></p> <p><span> </span></p> <p><strong><span>ABSTRACT</span></strong></p> <p><span><span> </span></span></p> <p><span>This article presents a bibliometric analysis of recent topics in ILS (Individual Learning Styles) research. The methodology employed was based on a systematic review of documents and scientific publications related to the study object from 2004 to the present utilizing the Scopus database and the 'bibliometrix' package in the R programming language. Several decision steps were followed to ensure the reliability and validity of the analysis. The findings allowed for the identification of the most cited journals, the most prominent authors, and the most common affiliations among the authors of the analyzed documents. Additionally, different models of learning style preferences and their impact on the teaching process were explored. The findings contribute significantly to understanding the dynamics of research in the studied discipline. Regarding the most cited journals, "Computers & Education" was found to be the leading journal in terms of the total number of citations, followed by "Educational Research Review" and "Learning and Instruction". As for the most prominent authors, several relevant names were identified, such as David Kolb, Richard Felder, and Peter Honey. Regarding the most common affiliations among the authors, it was found that several Spanish universities lead this list. On the other hand, this study explored different learning style models and their impact on the educational process. It was found that there is a wide variety of theoretical models on learning style, but there is no clear consensus on which model is best to apply in an educational context. However, the importance of considering students' learning styles to adapt the educational process to their individual needs was highlighted. In conclusion, this bibliometric analysis provides an overview of the current state of ILS research and can be useful for researchers, educators, and professionals interested in this field. The obtained results can also be used to identify current trends in ILS research and to guide future investigations in this area.</span></p>
Territorial land use data relative to Pesa Basin ( Tuscany) and its recent changes ( 2016- 2007)
<p>Data and elaborations are provided by IBIMET CNR , Accademia Georgofili and <a href="http://www.cbmv.it/">Consorzio di Bonifica 3 Medio Valdarno. </a></p>
A recent overview of the state-of-the-art elements of text classification - dataset
<p>The two available datasets were used to conduct the quantitative analysis of the text classification area. The set, such as:</p> <ol> <li>biblio.bib contains all articles that are grouped in categories</li> <li>biblio.csv contains processed records from biblio.bib, based on it were built the statistics presented in the article</li> </ol>
Data accessibility in the chemical sciences: an analysis of recent practice in organic chemistry journals
<div> <p>Data is the analysis of the data outputs of 240 randomly selected research papers from 12 top-ranked journals published in early 2023. We investigate author compliance with recommended (but not compulsory) data policies, whether there is evidence to suggest that authors apply FAIR data guidance in their data publishing, and if the existence of specific recommendations for publishing NMR data by some journals encourages compliance. Files in the data package have been provided in both human and machine-readable forms. The main dataset is available in the Excel file Data worksheet.XLSX, the contents of which can also be found in Main_dataset.CSV, Data_types.CSV, and Article_selection.CSV with explanations of the variable coding used in the studies in Variable_names.CSV, Codes.CSV, and FAIR_variable_coding.CSV. The R code used for the article selection can be found in Article_selection.R. Data about article types from the journals that contain original research data is in Article_types.CSV. Data collected for analysis in our sister paper[4] can be found in Extended_Adherence.CSV, Extended_Crystallography.CSV, Extended_DAS.CSV, Extended_File_Types.CSV, and Extended_Submission_Process.CSV. A full list of files in the data package and a short description for each is given in README.TXT.</p> </div>
Data related to: Hippocampal ripples and their coordinated dialogue with the default mode network during recent and remote recollection, Norman et al. (2021)
<p>This dataset contains intra-cranial EEG recordings and analysis code related to the paper: "Hippocampal ripples and their coordinated dialogue with the default mode network during recent and remote recollection" by Norman et al. (https://doi.org/10.1016/j.neuron.2021.06.020)<br> The study investigates the role of hippocampal ripples in the human brain during retrieval of recent and remote autobiographical memories and semantic facts. The intracranial recordings underwent standard preprocessing as described in the paper and were stored in EEGLAB datasets. The analysis code that accompanies the dataset implements the main analyses described in the paper.</p> <p>The dataset includes the following zip files:</p> <ul> <li>iEEG data and main analysis code: <ul> <li>“Norman_et_al_2021_iEEG_data_and_code_1.zip" </li> <li>“Norman_et_al_2021_iEEG_data_and_code_2.zip" </li> </ul> </li> <li>Patients' anatomical data: <ul> <li>“Norman_et_al_2021_Freesurfer.zip”</li> </ul> </li> <li>Additional toolboxes (developed by others): <ul> <li>“MATLAB_toolboxes.zip”</li> </ul> </li> </ul> <p>The code is written primarily in Matlab (version R2018b) and runs on a desktop computer with a 3.4Ghz Intel Core i7-6700 CPU with 64GB RAM. Matlab's Signal Processing Toolbox is required, as well as EEGLAB, Unfold toolbox, and several other open-source toolboxes.</p>
Macroevolutionary foundations of a recently-evolved innate immune defense
<p>There are two datasets along with accompanying statistical code used to generate the results of our article, the first is a database of published articles that from the basis of the literature review and then the other file contains data from an experimental study of phylogenetic conservation of peritoneal fibrosis in 17 species of ray-finned fish. Detailed description of the methodology can be found in the article (https://doi.org/10.1101/2020.07.08.191601).</p>
Data: Recent waning snowpack in the Alps is unprecedented in the last six centuries
<p><strong>Data_Dendro.txt</strong> contains the indexed ring-width chronology derived from living and relict common juniper (<em>Juniperus communis</em> L.) collected within or above the treeline in Ventina valley (46° 18’N, 9° 46’E). This data was used to reconstruct snowpack duration from 1400 to 2018 after calibration/validation with snow cover duration modelled from daily temperature and precipitation series.</p> <p><strong>Data_SALP_Reconstruction.txt</strong> contains the snow cover duration ring-width reconstruction (SALP) spanning from 1400 to 2018.</p> <p><strong>Data_Snow_cover_duration_south_Alps_1951_2018.txt</strong> contains the gridded 30’’ resolution snow cover duration over southern Alps for the period 1951-2018 as derived from a degree-day model applied to daily temperature and precipitation observations and calibrated on 312 snow depth observational series. This data was used to analyse the spatial signature of the indexed ring-width chronology.</p> <p><strong>Data_Time_serie_snow_cover_duration_Ventina.txt</strong> contains the snow cover duration series (period 1834-2018) derived for the specific location of the site chronology, obtained with a degree-day model applied to daily temperature and precipitation observations and calibrated on snow depth observational series. These data were used to calibrate/validate the snow cover reconstruction based on the indexed ring-width chronology.</p> <p>They are documented in the following article:</p> <p>Carrer, M., Dibona, R., Prendin, A. L., Brunetti,M., 2022. Recent waning snowpack in the Alps is unprecedented in the last six centuries. Nature Climate Change.</p>
Spatial predictions of suitable environments for palsas and peat plateaus in the Northern Hemisphere for recent and future periods
<p>Here we provide raster files of suitable environments for palsas and peat plateaus in the Northern Hemisphere. These files are results of a scientific study by Könönen et al. (2022, preprint). Files are provided in TIFF-format, and they describe the occurrence probability of the suitable environments for palsas and peat plateaus.</p> <p> </p> <p>Könönen, O. H., Karjalainen, O., Aalto, J., Luoto, M., and Hjort, J.: Environmental spaces for palsas and peat plateaus are disappearing at a circumpolar scale, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-135, in review, 2022.</p>
Taxonomy, distribution and classification of ecosystem-types, integrating the recent IUCN function-based typology and local conceptualizations
<p>1. Introduction:</p> <p>This dataset is a work in progress. It compiles data gathered on ecosystem-types and their distribution based on a series of field studies led by the author, in Seychelles and West and Central Africa (Senterre 2014, Senterre & Wagner 2014, Senterre 2016, Senterre et al. 2017, 2019, 2020, 2021a, 2022). The aims of this dataset are:</p> <p>a. To share in an explicit and transparent way data on proposed taxonomies of ecosystems, i.e. conceptualizations of ecosystem-types, including explicit ecosystem names and management of synonymies.</p> <p>b. To develop ecosystem red listing based on transparent and falsifiable distribution raw data, combining distribution modeling (maps) and in situ observation of individual stand occurrences.</p> <p>c. To illustrate in detail how to deal with ecosystem data following the approach described in Senterre et al. (2021b) (i.e. "ecosystemology" approach).</p> <p>d. To integrate the above approach with the newly developed function-based typology of ecosystems (Keith et al. 2022), therefore contributing to bridging the persistent gap between the global and the local scales in ecosystem descriptions and classifications.</p> <p> </p> <p>2. Context and versions:</p> <p>This dataset was initially planned for publication on GBIF (Global Biodiversity Information Facility), as part of a project developed for the review of Key Biodiversity Areas in Seychelles: "Mainstreaming recent species and ecosystem distribution data into Key Biodiversity Areas assessments in Seychelles" (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>).</p> <p>In the first version of the GBIF dataset (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>), we proposed an analysis of the potential 'core' and 'extension' files available in GBIF for a publication of ecosystem-type names (and synonymies) and their corresponding occurrences recorded from field observations. This is an original analysis of taxonomic principles managed entirely at the scale of local observable objects, and their history of identifications or interpretations.</p> <p>Toward the end of the above-mentioned GBIF project, considering the limitations and gaps currently present in GBIF, it was decided to restrict the GBIF dataset to a simple 'metadata' entry and to publish the complete version of this dataset in Zenodo. This allows to include all tables needed, as well as all required fields without having to accommodate them within the limited GBIF structure (see metadata description on GBIF for more details). The fields of the tables published here are described in the GBIF metadata entry and in the ecosystemology paper (Senterre et al. 2021b).</p> <p> </p> <p>3. New development on typology aspects:</p> <p>In addition, considering that the new IUCN global typology of ecosystems is now published (Keith et al. 2022), we have reviewed in detail the possibility of integration of ecosystems conceptualized using our ecosystemology approach within the new IUCN typology. The result of this analysis is being considered for a publication, and this Zenodo dataset would then be published in full (i.e. including all typology aspects) as supplementary materials. In the meantime, I would be happy to discuss any of these aspects with whoever is interested.</p> <p> </p> <p>4. Access to ecosystem data for conservation actors:</p> <p>Finally, the actual data (published here) on ecosystem-types, their names, synonymies, classification, distribution, and red list status are compiled into a format that we designed to be useful to conservation actors in the form of interactive webpages (produced with R as shiny apps). This development is based on very limited resources, and the author is still quite new to R, so any help or feedback on ways to improve the scripts would be very much welcomed.</p> <p>The interactive page is available here (currently filtered to Seychelles' data only, although the dataset contains data beyond the Seychelles): https://shiny.bio.gov.sc/bioeco/</p> <p>The R scripts are available on Github: https://github.com/bsenterre/ecosystemology</p> <p> </p> <p>5. Tables contained in this dataset:</p> <p>a. Ecosystem taxonomy tables:</p> <p>ecoSpecies: Contains the list of all ecosystem-type names with their unique identifier.</p> <p>ecoOccurrences: Contains the list of individual stand occurrences, including ecosystem characters as standardized in Senterre et al. (2021b; i.e. virtual ecosystem specimen).</p> <p>ecoSpeciesProfiles: Contains basic metadata on ecosystem-types, such as their Red List evaluations.</p> <p>ecoIdentifications: Contains all the different interpretations/identifications (referring to the table ecoSpecies or to higher levels of classification, see below) made on the stands observed in the ecoOccurrences table.</p> <p> </p> <p>b. Ecosystem typology tables (TO BE ADDED LATER):</p> <p>IUCNL3: This is just a transcription, as is, of the IUCN global typology version 2.1.</p> <p>IUCNL3BIOCrossover: This table defines and comments correspondences between BIOL2 (the level 2 of the typology used by us) and the IUCN typology L3 (level 3).</p> <p>BIOL2: This is a variation based on the IUCN typology, here our level 2.</p> <p>BIOL3: This is a variation based on the IUCN typology, here our level 3.</p> <p>BIOL4: This is a variation based on the IUCN typology, here our level 4.</p> <p>ecoGenus: This is a general type of stand (thus excluding any regional ecosystem connotation), defined at a local scale and never combined with any geographic connotation (see ecosystemology paper: Senterre et al. 2021b).</p> <p>ecoFamily: This is a generalized version of the ecoGenus (i.e. still excluding any regional, sub-regional or geographic aspect).</p> <p>ecoOrder: This is a further generalized version of the ecoGenus (see also Senterre et al. 2020).</p> <p>lifeZone: This is a basic and incomplete list of life zones as defined following the Holdridge (1967) approach, with some additional elements proposed in Senterre et al. (2021b).</p> <p> </p> <p>6. Literature cited:</p> <p>Holdridge, L. R. 1967. Life zone ecology. Tropical Science Center, San Jose, Costa Rica.</p> <p>Keith, D. A., J. R. Ferrer-Paris, E. Nicholson, M. J. Bishop, B. A. Polidoro, E. Ramirez-Llodra, M. G. Tozer, J. L. Nel, R. Mac Nally, E. J. Gregr, K. E. Watermeyer, F. Essl, D. Faber-Langendoen, J. Franklin, C. E. R. Lehmann, A. Etter, D. J. Roux, J. S. Stark, J. A. Rowland, N. A. Brummitt, U. C. Fernandez-Arcaya, I. M. Suthers, S. K. Wiser, I. Donohue, L. J. Jackson, R. T. Pennington, T. M. Iliffe, V. Gerovasileiou, P. Giller, B. J. Robson, N. Pettorelli, A. Andrade, A. Lindgaard, T. Tahvanainen, A. Terauds, M. A. Chadwick, N. J. Murray, J. Moat, P. Pliscoff, I. Zager, and R. T. Kingsford. 2022. A function-based typology for Earth’s ecosystems. . Nature 610:513–518. doi:10.1038/s41586-022-05318-4.</p> <p>Senterre, B. 2014. Mapping habitat-types within the Hummingbird site at Dugbe (Liberia, West Africa). Consultancy Report, Missouri Botanical Garden. P. 56. https://doi.org/10.13140/RG.2.2.32628.48003.</p> <p>Senterre, B. 2016. Habitat-type ground-truthing and assessment of ecosystem conservation value in the Bel Air Alufer mining site (Guinea, West Africa), with recommendations for improving the draft map of land cover types. Consultancy Report, Missouri Botanical Garden, A study conducted for Alufer Mining Limited. P. 54.</p> <p>Senterre, B., E. Bidault, and T. Stévart. 2019. Identification et évaluation des écosystèmes menacés du Mont Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 106. https://doi.org/10.13140/RG.2.2.13242.93129.</p> <p>Senterre, B., E. Bidault, T. Stévart, and P. P. Lowry II. 2020. Assessment of Key Biodiversity Areas in the Lofa-Gola-Mano & Nimba complexes (West Africa) using ecosystem criteria. Final Report, Missouri Botanical Garden. P. 146. 10.13140/RG.2.2.17934.89924.</p> <p>Senterre, B., E. Bidault, T. Stévart, M. Wagner, and P. Lowry. 2017. Mapping habitat-types in south-east Kouilou (Republic of Congo). Consultancy Report, Missouri Botanical Garden (MBG), Africa and Madagascar Department, St. Louis, Missouri, USA. P. 163.</p> <p>Senterre, B., R. M. Bristol, G. Gendron, and E. Henriette. 2021a. Fine-tuning conservation priorities in Seychelles at the landscape scale, using global KBA guidelines with both species and ecosystem criteria. Consultancy Report, United Nations Development Programme, GOS/UNDP/GEF Programme Coordination Unit, Victoria, Seychelles.</p> <p>Senterre, B., P. P. Lowry II, E. Bidault, and T. Stévart. 2021b. Ecosystemology: a new approach toward a taxonomy of ecosystems. . Ecological Complexity 47:100945. doi:https://doi.org/10.1016/j.ecocom.2021.100945.</p> <p>Senterre, B., A.-H. Paradis, E. Bidault, T. Stévart, and P. P. Lowry II. 2022. Qualité et distribution des savanes montagnardes du Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 73. http://dx.doi.org/10.13140/RG.2.2.13433.34401.</p> <p>Senterre, B., and M. Wagner. 2014. Mapping Seychelles habitat-types on Mahé, Praslin, Silhouette, La Digue and Curieuse. Consultancy Report, Government of Seychelles, United Nations Development Programme, Victoria, Seychelles. P. 119. https://doi.org/10.13140/RG.2.1.4558.6009.</p>
Data for: Patterns of shared signatures of recent positive selection across human populations
<p>Genome-wide summary stats for modified iHS scan in 1KG as reported in:</p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/29459708/">Patterns of shared signatures of recent positive selection across human populations.</a></p> <p>Johnson KE, Voight BF.Nat Ecol Evol. 2018 Apr;2(4):713-720. doi: 10.1038/s41559-018-0478-6. Epub 2018 Feb 19.</p> <p>PMID: 29459708</p> <p>Code available at: https://github.com/bvoightlab/iHS_calc</p>
Recent Increases in Tropical Cyclone Rapid Intensification Events in Global Offshore Regions
<p>The data and scripts in this repository can be used to support the main conclusion in the manuscript "Recent Increases in Tropical Cyclone Rapid Intensification Events in Global Offshore Regions" by Li et al., submitted to Nature Communications. The global distribution and annual variability of rapid intensification (RI) events of tropical cyclones (TCs) dervied from the open-source International Best Track Archive for Climate Stewardship (IBTrACS, https://www.ncei.noaa.gov/products/international-best-track-archive) are provided. The enviromental variables, including mid-level (600 hPa), vertical wind shear (200-850 hPa), and maximum potential intensity (MPI), were also calculated using the fifth generation of ECMWF reanalysis (ERA5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) forced in different scenarios. The python script (coastal_RI_submit ipynb) can be used to reproduce figures in the article.</p>
Data and analysis scripts for: Recent acceleration in global ocean heat accumulation by mode and intermediate waters
<p>The folder contains the MATLAB code and data to re-create Figures 1-9 and S1-3 within the publication by <em>Li, Z., England, M. H., & Groeskamp, S. Recent acceleration in global ocean heat accumulation by mode and intermediate waters, Nature Communications</em>, 2023.</p>
ScienceDex guides
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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.
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.