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1,751 results for “Future”
Projected changes in forest biomass to 2100 by county and species for 20 future scenarios
<p>Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously-derived growth and survival responses for 94 tree species, representing >90% of the contiguous U.S. forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found that averaged across temperature scenarios, the relative abundance of 60 species was projected to decrease by more than 5%, 20 species were projected to increase by more than 5%, and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of U.S. forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.</p>
Supplementary material 2 from: Rodrigues-Filho SJM, dos Santos Lobato F, Medeiros de Abreu CH, Rebelo MT (2023) Where in Europe is Chrysomya albiceps? Modelling present and future potential distributions. NeoBiota 85: 81-99. https://doi.org/10.3897/neobiota.85.96687
Occurrence points of Chrysomya albiceps recorded from the scientific literature and in the GBIF database
Supplementary material 1 from: Rodrigues-Filho SJM, dos Santos Lobato F, Medeiros de Abreu CH, Rebelo MT (2023) Where in Europe is Chrysomya albiceps? Modelling present and future potential distributions. NeoBiota 85: 81-99. https://doi.org/10.3897/neobiota.85.96687
References acquired from the databases cited in the manuscript and consulted in the literature review to generate a dataset of geographic coordinates of the species Chrysomya albiceps
Evolutionary adaptation of trees and modelled future larch forest extent in Siberia. Code and simulation data
<p>Code and datset used for the publication: "Evolutionary adaptation of trees and modelled future larch forest extent in Siberia" 2023 Gloy et al.</p>
Supplementary analysis 1 for Vitamin D status during adolescence and the impact of lifestyle changes – two years follow-up from the Fit Futures Study
<p>Supplementary analysis 1: multiple regression model including BMI instead of physical activity.</p>
Fig. 4 in An overview of acyclotides: Past, present and future
Fig. 4. Diversity in gene architecture of acyclotides from six angiosperm families (Violaceae, Rubiaceae, Fabaceae, Poaceae, Solanaceae, Cucurbitaceae). (ER- Endoplasmic Reticulum, NTPP- N terminal propeptide, NTR- N terminal repeat, CTPP- C terminal propeptide CTR- C terminal repeat, A1a- Albumin 1 domain -chain A).
Fig. 3 in An overview of acyclotides: Past, present and future
Fig. 3. Multiple Sequence Alignment of acyclotides. All acyclotides with D (Asp)/N(Asn) at C-terminal end are acyclic analogues of cyclotides, whereas those ending with stop codon (*) are genetically predetermined acyclotides.
Range contractions and reduced body mass predicted for endemic skinks of the Cameroon volcanic line with future warming
<p><em><span>Aim </span></em></p> <p><span>The vulnerability of montane species to environmental change has been increasingly recognized over the past decade. However, most of these species are regionally endemic with restricted ranges, limiting dispersal necessary for avoiding extinction. </span><span>Threats posed for montane lizards could be further complicated in species following Bergmann's rule, where body size increases with altitude.</span><span> In this study, we applied a bioclimatic and body mass trait-based species distribution model approach to identify areas suitable for montane endemic skink species of the Cameroon Volcanic Line (CVL) under current and future climates. </span></p> <p><em><span>Location</span></em></p> <p><span>Cameroon Volcanic Line</span></p> <p><em><span>Methods</span></em></p> <p><span>We recorded occurrence records and measured body mass in the field for skink species endemic to the CVL. We additionally supplemented our occurrence data with records from an online repository. We projected habitat suitability in the region by implementing the occurrence data in the bioclimatic species distribution models. We further integrated both occurrence and body mass information in our trait-based model to project potential body mass.</span></p> <p><em><span>Results</span></em></p> <p><span>Projected currently suitable ranges were limited to higher elevation regions, which are inhabited by numerous other threatened amphibian and reptile species. We found that, for our two skink species following Bergmann clines in body mass, trait model predictions covered a slightly larger geographic range than bioclimatic estimates. Under future warming, both models predict substantial contractions in suitable areas, potentially constraining species to mountain tops. Through the trait-based approach, we further detected potential warming-induced body mass reductions in projected suitable areas.</span></p> <p><em><span>Main conclusions</span></em></p> <p><span>We thus demonstrate how combining occurrence records with species trait information in predictive modelling can reveal complementary trends for more comprehensive climate change impact assessments. Overall, these challenges towards the persistence of CVL-endemic skink species should prompt urgent responses in national conservation management and local community engagement.</span></p>
Data and Code for the Manuscript: Aquatic insects balance growth with future supply of algal food resources
<p>Some consumers depend on the contemporaneous growth of the resources they feed on. For example, <em>Tanytarsus gracilentus</em> midges feed on algae, and because midge generation time is much longer than that of algae, midges benefit not just from the standing stock but also from the growth of algae. This implies that an intermediate consumption rate maximizes midge somatic growth: low consumption rates constrain midge growth, whereas high consumption rates reduce algae and future food abundance. In an experiment, we manipulated midge presence and initial algal abundance. We found that midges could suppress algal growth, as measured by changes in algal primary production (GPP). We also found a positive relationship between GPP and midge growth. We then fit a consumer-resource model to the experimental data, which showed the expected hump-shaped relationship between midge consumption rates and their somatic growth. In the model, projected midge growth rates were only positively associated with GPP when midge consumption was below the value that optimized midge growth. Therefore, the observed relationship between instantaneous primary production and midge growth seen in the experiment suggests that midges did not overexploit algae. This work highlights the challenges faced by consumers that depend on contemporaneously growing resources.</p>
Regionalized life cycle assessment of present and future lithium production for Li-ion batteries
<p>This dataset contains supplementary data for the following publication: </p> <p>Vanessa Schenker, Christopher Oberschelp, Stephan Pfister,<br> Regionalized life cycle assessment of present and future lithium production for Li-ion batteries,<br> Resources, Conservation and Recycling,<br> Volume 187,<br> 2022,<br> 106611,<br> ISSN 0921-3449,<br> https://doi.org/10.1016/j.resconrec.2022.106611.<br> (https://www.sciencedirect.com/science/article/pii/S0921344922004451)</p>
Supplementary Data: Trade-Offs in Land-Based Carbon Removal Measures under 1.5°C and 2°C Futures
<p>This compressed dataset includes the queried CVS files from 16 GCAM data bases generated for the study titled "<strong>Trade-Offs in Land-Based Carbon Removal Measures under 1.5°C and 2°C Futures</strong>".</p> <p>The data sets provided here came from the GCAM model output. Please find the model and code information at the GitHub repo: <a href="https://github.com/realxinzhao/paper-LandBasedCDR-GCAM">realxinzhao/paper-LandBasedCDR-GCAM</a>.</p> <p>In addition, the data were used for generating results used in the paper. See more information at <a href="https://github.com/realxinzhao/paper-LandBasedCDR-DisplayItems">realxinzhao/paper-LandBasedCDR-DisplayItems</a>.</p>
Estuarine Hypoxia – Identifying High Risk Catchments Now and Under Future Climate Scenarios - Water Level Dataset
<p>Historic water level data used in determining the inundation characteristics for each of the catchments within the study area. The locations of each water level gauge, a summary of the distribution of water levels and the distribution of data to each catchment is detailed in the Supporting Information accompanying the manuscript "Estuarine Hypoxia – Identifying High Risk Catchments Now and Under Future Climate Scenarios".</p>
Figure 2 in Future of DNA-based insect monitoring
Figure 2. The four crucial areas where concerted actions are required are (i) DNA reference database generation to fill the dark taxa barcode gaps, (ii) a collective framework for method standardisation and the identification of gold-standard tools and indices for terrestrial monitoring, (iii) scaling up monitoring efforts by lowering the barrier to participation through citizen science engagement and technological developments, and (iv) integration of molecular tools with non-genetic monitoring technologies to scale up insect monitoring and retrieve biomass and sex information simultaneously (middle panel). Abbreviation: LIDAR, laser imaging, detection, and ranging.
Figure I in Future of DNA-based insect monitoring
Figure I. Standing on the shoulders of giants – three significant pioneering research developments have paved the way for DNA-based insect monitoring: the discovery of DNA barcoding for species identification, bulk insect metabarcoding for large-scale and rapid species identification, and overcoming PCR biases with PCR-free shotgun metagenomics. Abbreviation: mtDNA, mitochondrial DNA.
Bibliometric Analysis of Data Mining Techniques in Human Motion Research: Future Directions
<p>bibliometric dataset</p>
Monday 4 May: Web archives as a critical method for the future of digital research, Matthew Weber
<p>Monday 4 May: Web archives as a critical method for the future of digital research, Matthew Weber</p> <p>Matthew S. Weber, Associate Professor in the Hubbard School of Journalism and Mass Communication at the University of Minnesota</p>
Future Riverine Flood Impacts for NUTS3 regions in Europe: GLOFRIS input to DIFI
<p>This dataset presents results of current and future riverine flood impact data for NUTS3 regions in Europe. The dataset has been developed following the methodology presented in Tiggeloven et al. (2020) and Mortensen et al. (In Review).</p><p>This dataset can be used to as direct input for the DIFI model as described in Tesselaar et al. (2023).</p><p>References:</p><p>Mortensen, E., Tiggeloven, T., Haer, T., van Bemmel, B., Bouwman, A., Ligtvoet, W., & Ward, P.J.: The potential for various riverine flood DRR measures at the global scale. <i>Journal of Coastal and Riverine Flood Risk</i>, In Review.</p><p>Tesselaar, M., Botzen, W.J.W., Aerts, J.C.J.H., Tiggeloven, T. (2023). Flood insurance is a driver of population growth in European floodplains. <i>Nature Communications (provisionally accepted)</i></p><p>Tiggeloven, T., De Moel, H., Winsemius, H. C., Eilander, D., Erkens, G., Gebremedhin, E., ... & Ward, P. J. (2020). Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures. <i>Natural Hazards and Earth System Sciences</i>, <i>20</i>(4), 1025-1044.</p>
Early Feasibility Study of the NORM™ System in Heart Failure Patients (FUTURE-HFII)
ClinicalTrials.gov study NCT05763407. IPD Sharing: NO. Countries: 1. Publications: 0.
Blood Cell Collection for Future Use in Individuals With Fanconi Anemia
ClinicalTrials.gov study NCT00271089. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF): Pilot Study
ClinicalTrials.gov study NCT05898165. IPD Sharing: NO. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.