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601 results for “Global changes”
Data for: Plant-soil biota interactions explain shifts in plant community composition under global change
<p>1. Plant-soil biota interactions play a crucial role in the assembly of plant communities and the maintenance of plant species diversity. However, few studies have tested how the effect of soil biota on plant species and communities depend on environmental context and whether shifts in plant community composition caused by environmental change are associated with variation in plant-soil biota interactions. 2. We combined a field experiment in a Tibetan alpine meadow and a greenhouse experiment with factorial combinations of nitrogen (N) enrichment and warming to examine the role of plant-soil biota interactions in plant community dynamics. 3. The results showed that plant relative abundances were negatively correlated with the net effects of soil biota on plant growth but only under ambient field conditions. Warming and N-enrichment alleviated the negative soil biota effects in the greenhouse, and changed plant community composition and reduced species diversity in the field. Importantly, changes in soil biota effects on plant growth were positively correlated with changes in plant relative abundances caused by warming and N-enrichment in field. In a parallel field experiment, the diversity of mycorrhizal fungi increased while the diversity of fungal pathogens remained unchanged under warming and N-enrichment, indicating that soil biodiversity may play a critical role in plant responses to environmental change. 4. This study empirically demonstrates that altered plant-soil biota interactions explain shifts in plant community composition under global change, providing new insights into the mechanisms of diversity loss in a changing world.</p>
Intermediate data belonging to "Process-based climate change assessment for European winds using EURO-CORDEX and global models"
<p>This dataset contains the intermediate results of Wohland (2022) that are needed to redo the analysis und produce the figures. It allows to bypass those steps that rely on access to the supercomputers at the German Climate Computing Centre (DKRZ). When using this data in academic work, please reference</p> <blockquote> <p>Jan Wohland, Process-based climate change assessment for European winds using EURO-CORDEX and global models, Environmental Research Letters (provisionally accepted on 28/11/2022), 2022</p> </blockquote> <p><strong>Using this data to reproduce results</strong></p> <p>The data can be used together with the code provided in https://github.com/jwohland/kliwist_modelchain</p> <p>In the above mentioned github repository, there is a `run_all.py` script that repeats the analysis presented in Wohland (2022). After downloading and extracting this data, you can ignore the steps under "calculations", and begin with "plots".</p> <p><strong>Underlying data</strong></p> <p>The dataset draws on output from the CMIP5, CMIP6 and EURO-CORDEX initiatives. I thank the climate modeling groups for making their data openly available. In particular, I acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. I also acknowledge the Earth System Grid Federation infrastructure an international effort led by the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP). I also acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6.</p> <p><strong>Funding</strong></p> <p>This work is part of the project "The influence of climate change on wind energy site assessments – KliWiSt" funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK).</p> <p><strong>References to raw data journal articles</strong></p> <blockquote> <p>Jacob, D. <em>et al.</em> EURO-CORDEX: new high-resolution climate change projections for European impact research. <em>Reg Environ Change</em> <strong>14</strong>, 563–578 (2014).</p> </blockquote> <blockquote> <p>Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An Overview of CMIP5 and the Experiment Design. <em>Bull. Amer. Meteor. Soc.</em> <strong>93</strong>, 485–498 (2012).</p> </blockquote> <blockquote> <p>Hurtt, G. C. <em>et al.</em> Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. <em>Climatic Change</em> <strong>109</strong>, 117–161 (2011).</p> </blockquote>
CMIP6 data for the analysis in the article "Storylines of Maritime Continent dry period precipitation changes under global warming"
<p>The files include the data required to generate the figures based on CMIP6 model simulation outputs</p>
Data for: Global change risks a threatened species due to alteration of predator-prey dynamics
<p>Datasets generated and analyzed within the study area located in the Côte-Nord region of Québec, Canada. To identify species-specific movement rules that were implemented in the IBM, we used empirical data collected for caribou, moose, and wolves over the study area.</p> <p>"DataFinal_SSF_Species_season.csv" (6 files) were used to develop Step Selection Functions for caribou, moose, and wolves to assess habitat selection. <span>SSFs</span><span> were estimated from data for the real animals and provide the relative probability of selection among a set of options based on the comparison of observed and random steps (i.e., the linear segment between successive locations at 8-h interval) using conditional</span><span> logistic regression </span><span>(Fortin et al. 2005). Details on GPS data and SSF models can be found in the article in Appendix S1: Section S2. </span></p> <p>SSFs compare resource characteristics of observed (scored 1) and random (scored 0) locations presented in column case. Habitat characteristics (columns conif_dense, conif_open, mixed, open, other, fire010, fire1020, fire20, cut010, cut1020, cut20) was extracted from the Canadian National Forest Inventory (NFI) forest cover maps. Land cover maps were updated every year by adding roads, recent (<5 years), regenerating (6–20 years) and old (21–50 years) cutblocks/fires based on information provided annually by local forestry companies and from the Canadian National Fire Database (CNFDB). Columns dist0_0.25, dist0.25_0.50, dist0.5_1.00, dist1.00_1.5, and dist1.5 are a set of 5 dichotomous covariables representing the classes of distance to the nearest road (i.e., 1) ≤250 m, 2) 251–500 m, 3) 501–1000 m, 4) 1001–1500 m and 5) >1500 m as the reference category).</p> <p>"DataFinal_IBM_Caribou_Season.csv" (2 files) corresponded to the IBM outputs with the proportion of caribou agent killed (Prop.Caribou_killed, number of caribou killed/total number of caribou), in function of the different scenarios (CC,LUC,Year,Season,Scenario) and the response (Behavioral-Numerical responses or Behavioral response). The columns Prop.CutsRoads, Prop.Fire, Prop.Broadleaf, Homogenization, Isolation correspond to the different variable we tested to predict the cumulative impact of anthropogenic disturbance and climate change. To explore how changes in forest structure and composition impacted the proportion of caribou killed, we used the proportion of areas disturbed by cuts and roads (Prop.CutsRoads), burned areas (Prop.Fire), and landscape characteristics, such as the proportion of deciduous vegetation (Prop.Broadleaf), landscape homogenization (Homogenization) and isolation (Isolation) of mature conifer stands.</p>
Data for: Coral adaptive capacity insufficient to halt global transition of coral reefs into net erosion under climate change
<p>Projecting the effects of climate change on net reef calcium carbonate production is critical to understanding the future impacts on ecosystem function, but prior estimates have not included corals' natural adaptive capacity to such change. Here we estimate how the ability of symbionts to evolve tolerance to heat stress, or for coral hosts to shuffle to favourable symbionts, and their combination, may influence responses to the combined impacts of ocean warming and acidification under three representative concentration pathway emissions scenarios (RCP2.6, RCP4.5, RCP8.5). We show that symbiont evolution and shuffling both individually and when combined favours persistent positive net reef calcium carbonate production. However, our projections of future net calcium carbonate production under climate change vary both spatially and by RCP. For example, 19–35% of modelled coral reefs are still projected to have net positive net calcium carbonate production by 2050 if symbionts can evolve increased thermal tolerance, depending on the RCP. Without <span>symbiont adaptive capacity,</span> the number of coral reefs with positive net calcium carbonate production drops to 9–13% by 2050. Accounting for both symbiont evolution and shuffling, we project median positive net calcium carbonate production of coral reefs will still occur under low greenhouse emissions (RCP2.6) in the Indian Ocean, and even under moderate emissions (RCP4.5) in the Pacific Ocean. However, adaptive capacity will be insufficient to halt the transition of coral reefs globally into erosion by 2050 under severe emissions scenarios (RCP8.5).</p>
Projections of changes in the global distribution of shallow water ecosystems through 2100 due to climate change
<p>The global area and distribution of shallow water ecosystems (SWEs), and their projected responses to climate change, are fundamental for evaluating future changes in their ecosystem functions, including biodiversity and climate change mitigation and adaptation. Although previous studies have focused on a few SWEs, we modelled the global distribution of all major SWEs (seagrass meadows, macroalgal beds, tidal marshes, mangroves, and coral habitats) from current conditions (1986−2005) to 2100 under the representative concentration pathway (RCP) 2.6 and 8.5 emission scenarios. Our projections show that global coral habitat shrank by as much as 75% by 2100 with warmer ocean temperatures, but macroalgal beds, tidal marshes, and mangroves remained about the same because photosynthetic active radiation (PAR) depth did not vary greatly (macroalgal beds) and the shrinkage caused by sea-level rise was offset by other areas of expansion (tidal marshes and mangroves). Seagrass meadows were projected to increase by up to 11% by 2100 because of the increased PAR depth. If the landward shift of tidal marshes and mangroves relative to sea-level rise was restricted by assuming coastal development and land use, the SWEs shrank by 91.9% (tidal marshes) and 74.3% (mangroves) by 2100. Countermeasures may be necessary for coastal defense in the future; these include considering the best mix of SWEs and coastal hard infrastructure because the significant shrinkage in coral habitat could decrease wave energy. However, if appropriate coastal management is achieved, the other four SWEs, which have relatively high CO<sub>2</sub> absorption rates, can help mitigate the climate change influences.</p>
Global Changes Associated With Sacroiliac Joint Dysfunction
ClinicalTrials.gov study NCT06687148. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Gait Pattern and Experienced Global Change After Shunt Surgery in Idiopathic Normal Pressure Hydrocephalus
ClinicalTrials.gov study NCT04795089. IPD Sharing: UNDECIDED. Countries: 1. Publications: 28.
Longitudinal Changes in Left and Right Ventricular Global Strain After Chemotherapy in Cardiac Light Chain Amyloidosis
ClinicalTrials.gov study NCT05452850. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Local adaptation in a marine foundation species: implications for resilience to future global change
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Soil carbon, nitrogen, and phosphorus cycling microbial populations and their resistance to global change depend on C:N:P stoichiometry
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Data from: Melanin-based colouration and host-parasite interactions under global change
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Contrasting responses of different functional groups stabilise community responses to a dominant shrub under global change
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Data from: Going with the flow: the role of ocean circulation in global marine ecosystems under a changing climate
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Data from: Trade-offs and synergies between bird conservation and wildfire suppression in the face of global change
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Data from: Mediating water temperature increases due to livestock and global change in high elevation meadow streams of the Golden Trout Wilderness
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Data from: Deep-sea ostracod faunal dynamics in a marginal sea: Biotic response to oxygen variability and mid-Pleistocene global changes
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Data from: Woody encroachment over 70 years in South African savannas: overgrazing, global change or extinction aftershock?
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Data from: Global pattern of nest predation is disrupted by climate change in shorebirds
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Data from: An operational definition of the biome for global change research
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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.