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133 results for “climate sensitivity”
Data and analysis and plotting scripts for Swaminathan et al., "Regional Impacts Poorly Constrained by Climate Sensitivity"
<p>The datasets included here are of the plotted data from the figures of the paper entitled "Regional Impacts Poorly Constrained by Climate Sensitivity", by Ranjini Swaminathan, Jacob Schewe, Jeremy Walton, Klaus Zimmermann, Colin Jones, Richard A. Betts, Chantelle Burton, Chris D. Jones, Matthias Mengel, Christopher Reyer, Andrew G. Turner & Katja Weigel, submitted for publication in Earth's Futures. Scripts used for plotting and analysis are also included.</p>
CESM2 simulation output used in the study "On the links between ice nucleation, cloud phase, and climate sensitivity in CESM2"
<p>Provided is all CESM2 model output used to generate figures in the study, for which a preprint is at 'https://doi.org/10.22541/essoar.167214452.25853014/v1'. File names indicate the experiment names used in the study. For each model experiment, there is one file containing variables in a present-day (PD) simulation, plus a second file containing cloud feedbacks calculated by the Zelinka et al 2012 kernel method (comparing PD to PD with 4K warming uniformly added to sea surface temperatures).</p>
Habitat and climatic associations of climate-sensitive species along a southern range boundary
<p><span class="Dummy">Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate‐sensitive vertebrates along a southern range boundary <span>in Northern Michigan, USA</span>. We combined multiple sources of occurrence data, including harvest and citizen‐science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate‐sensitive vertebrate species (American marten [</span><em><span class="fi">Martes americana</span></em><span class="Dummy">], snowshoe hare [</span><em><span class="fi">Lepus americanus</span></em><span class="Dummy">], ruffed grouse [</span><em><span class="fi">Bonasa umbellus</span></em><span class="Dummy">], and moose [</span><em><span class="fi">Alces alces</span></em><span class="Dummy">]). We used total basal area of at‐risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce‐fir and lowland riparian forest types, hares with lowland conifer and aspen‐birch, grouse with lowland riparian hardwood</span><span>s</span><span>, </span><span class="Dummy">and moose with upland spruce‐fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures, and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce‐fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate‐sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy‐relevant scales</span><span class="Dummy">.</span></p>
Data used in: Phenological sensitivities to climate are similar in two Clarkia congeners: Indirect evidence for facilitation, convergence, niche conservatism, or genetic constraints
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Habitat and climatic associations of climate-sensitive species along a southern range boundary
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Data and code from: Western larch regeneration more sensitive to wildfire-related factors than seasonal climate variability
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Data from: Large, climate-sensitive soil carbon stocks mapped with pedology-informed machine learning in the North Pacific coastal temperate rainforest
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Data from: Grassland restoration drives strong multitrophic biodiversity recovery, but climate extremes jeopardize drought-sensitive species
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Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants
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Analysis of vegetation distribution in interior Alaska and sensitivity to climate change using a logistic regression approach
All data are used in the following manuscript which is in prep Analysis of vegetation distribution in interior Alaska and sensitivity to climate change using a logistic regression approach Calef et al.
Repository for: Reddin et al. 2020. Marine clade sensitivities to climate change conform across time scales
<p>Contains R code and data to produce the main results (and some supplementary results) of the publication, Reddin et al. <em>Marine clade sensitivities to climate change conform across time scales</em>.</p>
Data from: Marine latitudinal diversity gradients, niche conservatism, and out of the tropics and Arctic: climatic sensitivity of small organisms
<ul> <li>Aim</li> </ul> <p>The latitudinal diversity gradient (LDG) is a consequence of evolutionary and ecological mechanisms acting over long history, and thus is best investigated with organisms that have rich fossil records. However, combined neontological-paleontological investigations are mostly limited to large, shelled invertebrates, which keeps our mechanistic understanding of LDGs in its infancy. This paper aims to describe the modern meiobenthic ostracod LDG and to explore the possible controlling factors and the evolutionary mechanisms of this large-scale biodiversity pattern.</p> <ul> <li>Location</li> </ul> <p>Present-day Western North Atlantic</p> <ul> <li>Taxon</li> </ul> <p>Ostracoda</p> <ul> <li>Methods</li> </ul> <p>We compiled census data from ostracods living in shallow marine environments of the western North Atlantic Ocean. Using these data, we documented the marine LDG with multiple metrics of alpha, beta (nestedness and turnover), and gamma diversity, and we tested whether macroecological patterns could be governed by different environmental factors, including temperature, salinity, dissolved oxygen, pH and primary productivity. We also explored the geologic age distribution of ostracod genera to investigate the evolutionary mechanisms underpinning the LDG.</p> <ul> <li>Results</li> </ul> <p>Our results show that temperature and climatic niche conservatism are important in setting LDGs of these small, poorly-dispersing organisms. We also found evidence for some dispersal-driven spatial dynamics in the ostracod LDG. Compared to patterns observed in marine bivalves, however, dispersal dynamics were weaker and they were bi-directional, rather than following the "out-of-the-tropics" model.</p> <ul> <li>Main Conclusions</li> </ul> <p>Our detailed analyses revealed that meiobenthic organisms, which comprise two-thirds of marine diversity, do not always follow the same rules as larger, better-studied organisms. Our findings suggest that the under-studied majority of biodiversity may be more sensitive to climate than are well-studied, large organisms. This implies that the impacts of ongoing Anthropocene climatic change on marine ecosystems may be much more serious than presently thought.</p>
Dataset from the project entitled HimFunDiff. Related to research article: Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity.
<p>We examined a total of 9 populations of Rhododendron anthopogon, which were located between 3200 m and 4200 m above sea level (asl). These populations were distributed across three geographically distant transects, with each transect consisting of three sites (along an elevation gradient). The transects are referred to as northern, intermediate, and southern, while the sites at each transect are categorized as low, mid, and high (as depicted in Thakur et al 2024). The northern transect exhibited colder temperatures and lower rainfall compared to the other two transects. On the other hand, the two remaining transects had relatively similar temperatures, but the southernmost transect received higher levels of precipitation. The mean annual temperature of these populations ranged from 2 °C to 5 °C from 2021 through 2022, while volumetric soil moisture levels varied from 0.198 to 0.377 based on onsite measurements using TMS4 dataloggers (Wild et al., 2019).</p> <p>We collected a total of 81 wood disc samples, with 9 samples obtained from each of the 9 sites studied (9 populations × 9 discs). The samples were collected by cutting a single piece from the thickest stem segment, approximately 5 cm in length, from 81 different mature and healthy individuals. Within each site, the 9 samples were obtained from three separate plots (three samples per plot), each covering an area of approximately 100 m2. The selection criteria for these plots included: (1) the presence of Rhododendron anthopogon as one of the dominant species; (2) minimal anthropogenic disturbance; and (3) the absence of large shrubs or trees. The sampled individuals within a plot were spaced at least 5 m apart from each other, and the plots themselves were at least 20 m apart. To prevent rapid drying, the cut stem samples were immediately placed in a wet paper towel. Within 48 hours of sampling, the stem samples underwent dehydration by being immersed in 50 % ethanol for the initial 3 days, followed by 70 % ethanol for the subsequent 7 to 10 days. After the ethanol dehydration process, the samples were air-dried for 72 hours and then stored in paper bags until further processing.</p> <p>Plant age and growth data for each of the sampled individuals were obtained following established protocols (Doležal et al., 2018). In the laboratory, we utilized a sledge microtome to cut cross-sections from each stem sample. These cross-sections were then stained with Astra Blue and Safranin and permanently affixed to microscope slides using Canada Balsam (Doležal et al., 2022). High-resolution images of the fixed sections were captured using an Olympus BX53 microscope equipped with an Olympus DP73 camera. The software CellSense Entry 1.9 was employed to analyse the best image obtained from each individual. We measured annual radial growth increments from pith to bark to the nearest micrometre. </p> <p>More details are given in the article entitled </p> <h1>Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170252" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.scitotenv.2024.170252</a></h1>
Datasets for "Peatland evaporation across hemispheres: contrasting controls and sensitivity to climate warming driven by plant functional types" - Version 2
<p>Version 2 of datasets used for analyses in the paper titled "Peatland evaporation across hemispheres: contrasting controls and sensitivity to climate warming driven by plant functional types" submitted to Biogeosciences. There are two datasets - one from Kopuatai bog, Aotearoa New Zealand, and one from Mer Bleue bog, Canada - which contain gap-filled and filtered data that were used to produce the results of our study.</p> <p>Due to improvements made to our methodology following the paper peer review process, the data in this version slightly differs from that of the previous version. Information on these revisions can be found in the README file below or the Discussion/Peer Review tab of our paper.</p> <p> </p> <p> </p>
Data from: Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity
<p>The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR) – key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO<sub>2</sub> forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades, and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.</p>
Supporting Data for "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change"
<p>Code and netcdf files of processed X-SHiELD and CMIP6 simulations to reproduce the figures of Timothy M. Merlis, Kai-Yuan Cheng, Ilai Guendelman, Lucas Harris, Christopher S. Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K. Clark, Gabriel A. Vecchi, and Stephan Fueglistaler (2024): "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change".</p>
The more the merrier - Multi-frequency magnetic susceptibility of loess and palaeosols as a sensitive climate proxy
<p>This data set (updated 2025) contains: </p> <p><strong>A) Data</strong></p> <p>1) Summary files of the central data sets as Microsoft Excel worksheets</p> <ul> <li>Multi-frequency DynoMag data for section Khonako-II (<em>KH-II_chiBFD.xlsx)</em></li> <li>Dual-frequency Kappabridge data for section Khonako-II (<em>KH-II_full_profile_Kappa.xlsx</em>)</li> </ul> <p>2) Temperature-dependent magnetic susceptibility data in folder<em> k(T).zip</em></p> <p>3) Remanence measurement data in folder<em> remanence.zip</em></p> <p>4) Temperature-dependent magnetic susceptibility data measured at three frequencies using a Quantum Design Magnetic Properties Measurement System (<em>SQUID.zip</em>)</p> <p>5) Multi-frequncy magnetic susceptibilty data for different sites (<em>MFMS_data.zip</em>)</p> <p>6) Raw data files of dual-frequency DynoMag data for section Khonako-II (<em>KH-II_section.zip)</em></p> <p><strong>B) R code files</strong></p> <p>1) R code to correct hysteresis loops from MPMS data for paramagentic contributions and to extract values of coercivity and exchange bias (<em>magnetic_hysteresis_suppl_mat.R</em>). The data files used in this code are stored in folder <em>mass-corrected_MPMS.zip.</em></p> <p>2) R code to calculate magnetic particle size distributions from multi-frequency magnetic susceptibility data measured on the Dynomag instument and temperature-dependent magnetic susceptibility data measured at three frequencies using a Quantum Design Magnetic Properties Measurement System (<em>particle_size_calculation.R</em>). The data files used in this code are stored in folder <em>particle_size_distribution.zip</em>.</p>
Contrasting sensitivity of weathering proxies to Quaternary climate and sea-level fluctuations on the southern slope of the South China Sea
<p>Tropical marginal seas host important sedimentary archives that may be exploited to reveal past changes in continental erosion, chemical weathering, and ocean dynamics. However, these records can be challenging to interpret due to the complex interactions between climate and particulate transport across ocean margins. For the southern South China Sea over the last 90 kyr, we observe a contrasting temporal relationship between the deposition of clay minerals and magnetic minerals, which were associated with two different hydrodynamic modes. Fine-grained clay minerals can be carried in suspension by ocean currents, leading to a rapid response to regional climate-driven inputs. In contrast, changes in magnetic mineralogy were linked to glacial-interglacial sea-level variability, from which we infer a control by bedload transport and resuspension. Overall, this study indicates that the transfer pathways and mechanisms imparted by varying hydrodynamic conditions exert a substantial influence on the distribution of terrigenous material in continental margin sediments.</p>
How melanism affects the sensitivity of lizards to climate change
<p>The impact of climate change on global biodiversity is firmly established, but the differential effect of climate change on populations within the same species is rarely considered. In ectotherms, melanism (i.e. darker integument due to heavier deposition of melanin) can significantly influence thermoregulation, as dark individuals generally heat more and faster than bright ones. Therefore, darker ectotherms might be more susceptible to climate change. Using the color-polyphenic lizard <em>Karusasaurus polyzonus</em> (Squamata: Cordylidae), we hypothesized that, under future climatic projections, darker populations will decrease their activity time more than brighter ones due to their greater potential for overheating. To test this, we mechanistically modeled the body temperatures of 56 individuals from five differently-colored populations under present and future climate conditions. We first measured morphological traits and integumentary reflectance from live animals, and then collected physiological data from the literature. We used a biophysical model to compute activity time of individual lizards as proxy for their viability, and thereby predict how different populations will cope with future climate conditions. Contrary to our expectations, we found that all populations will increase activity time and, specifically, that darker populations will become relatively more active than bright ones. This suggests that darker populations of <em>K. polyzonus</em> may benefit from global warming. Our study emphasizes the importance of accounting for variation between populations when studying responses to climate change, as we must consider these variations to develop efficient and specific conservation strategies.</p>
CESM1-SOM Climatologies used for "Climate Sensitivity is Sensitive to Changes in Ocean Heat Transport" (published in Journal of Climate, Mar 2022)
<p>CESM1-SOM climatologies.</p> <p>Pre-industrial control run = SOM_Control.cam5.0030-0059.ann.nc</p> <p>CO2-doubling experiments:</p> <ul> <li>OHT + 30% = SOM_OHFC_P30_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT + 15% = SOM_OHFC_P15_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>Control OHT = SOM_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT - 15% = SOM_OHFC_M15_2XCO2_032019.cam5.0030-0059.ann.nc</li> <li>OHT - 30% = SOM_OHFC_M30_2XCO2_032019.cam5.0030-0059.ann.nc</li> </ul>
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.