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Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CSIRO.ACCESS-ESM1-5.esm-hist' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Earth System Model Version 1.5 climate model, released in 2019, includes the following components: aerosol: CLASSIC (v1.0), atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m), land: CABLE2.4, ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), ocnBgchem: WOMBAT (same grid as ocean), seaIce: CICE4.1 (same grid as ocean). The model was run by the Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (CSIRO) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CSIRO-ARCCSS.ACCESS-CM2.ssp245' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Climate Model Version 2 climate model, released in 2019, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: CABLE2.5, ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE5.1.2 (same grid as ocean). The model was run by the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science). Mailing address: CSIRO, c/o Simon J. Marsland, 107-121 Station Street, Aspendale, Victoria 3195, Australia (CSIRO-ARCCSS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.

Understanding variation in the diet of widely distributed species can help us to predict how they respond to future environmental and anthropogenic changes. We studied the diet of the red fox Vulpes vulpes, one of the world’s most widely distributed carnivores. We compiled dietary data from 217 studies at 276 locations in five continents to assess how fox diet composition varied according to geographic location, climate, anthropogenic impact and sampling method. The diet of foxes showed substantial variation throughout the species’ range, but with a general trend for small mammals and invertebrates to be the most frequently occurring dietary items. The incidence of small and large mammals and birds in fox diets was greater away from the equator. The incidence of invertebrates and fruits increased with mean elevation, while the occurrence of medium-sized mammals and birds decreased. Fox diet differed according to climatic and anthropogenic variables. Diet richness decreased with increasing temperature and precipitation. The incidence of small and large mammals decreased with increasing temperature. The incidence of birds and invertebrates decreased with increasing mean annual precipitation. Higher Human Footprint Index was associated with lower incidence of large mammals and higher incidence of birds and fruit in fox diet. Sampling method influenced fox diet estimation: estimated percentage of small and medium-sized mammals and fruit was lower in studies based on stomach contents, while large mammals were more likely to be recorded in studies of stomach contents than in studies of scats. Our study confirms the flexible and opportunistic dietary behaviour of foxes at the global scale. This behavioural trait allows them to thrive in a range of climatic conditions, and in areas with different degrees of human-induced habitat change. This knowledge can help place the results of local-scale fox diet studies into a broader context and to predict how foxes will respond to future environmental changes. Castañeda et al. 2022 Mammal Review (Variation in red fox Vulpes vulpes diet in five continents)

A Calypso Square gravity core AMD15-Casq1 (543 cm) and corresponding box core (40 cm) were collected in 2015 from the central north NOW (77°15.035’ N, 74°25.500’ W, 692 m water depth) (Figure 1) during the ArcticNet Leg 4a, onboard the Canadian Coast Guard Ship Amundsen. Core chronology: The core chronology is based on 11 accelerator mass spectrometry (AMS) dates on mollusc shells from the Calypso core, and 210Pb and 137Cs measurements on 20 samples from the box core (see Jackson et al. (2021) for more details). Here, all radiocarbon dates were calibrated using the latest marine calibration curve (Marine20; Heaton et al., 2020; Table S1). In Jackson et al. (2021), and using the Marine13 calibration curve, a local reservoir correction of 140 ± 60 years was applied based on measurements from a live marine mollusc specimen collected from the NOW before the mid-1950’s (McNeely & Brennan, 2005). Using the Marine20 calibration curve, this specimen now yields a reservoir offset of –4 ± 60 years. In line with this reduced reservoir offset for the Marine 20 (vs. Marine13) calibration curve, and owing to the lack of a regional ΔR term for the polynya (Pieńkowski et al., 2023), no additional reservoir age correction (i.e., ΔR=0) was applied. A mixed age-depth model was constructed using the bacon-package in R (Blaauw & Christen, 2011). Accordingly, the composite core covers the last ca. 3800 cal years BP. We note that the new calibration only resulted in negligible changes compared to the age model presented in Jackson et al. (2021). Diatom analyses: Sediment samples for diatom analysis were prepared following the protocol described in Crosta et al. (2020). Approximately 0.3 g of dry sediment was treated with an oxidative solution composed of hydrogen peroxide (H2O2), distilled water and tetrasodium pyrophosphate (decahydrate, Na4O7P2-10H2O) in a warm bath (~65°C) for several hours until the reaction ceased. The residue was then rinsed repeatedly with distilled water by centrifugation (7 min at 1200 rpm). Hydrochloric acid (HCl, 30%) was used to remove the carbonate content. The residue was again rinsed several times until neutral pH, and microscopy slides were mounted in Naphrax©. In each sample, ca. 300 diatom valves were identified to the lowest taxonomic level possible. Resting spores of Chaetoceros were counted, but not included in the relative abundance calculations. Census counts were done using a light microscope (Olympus BX53, UNB) with dark field, phase contrast optics and oil immersion, at 1000X magnification. We followed the counting rules presented in Crosta and Koç (2007): specimens were counted when at least half of the valve was observed, with the exception of Rhizosolenia and Thalassiothrix taxa that were only counted when the spine-like proboscis or appendix was visible, respectively. The Pikialasorsuaq (North Water polynya) is an area of local and global cultural and ecological significance. However, over the last decades, the region has been subject to rapid warming and, in some recent years, the seasonal ice arch that has historically defined the polynya’s northern boundary has failed to form. Both factors are deemed to alter the polynya’s ecosystem functioning. To understand how climate-induced changes to the Pikialasorsuaq impact the basis of the marine food web, we explored diatom community-level responses to changing conditions, from a sediment core spanning the last 3800 years. Four metrics were used: total diatom concentrations, taxonomic composition, mean size, and diversity. Generalized additive model statistics highlight significant changes at ca. 2400, 2050, 1550, 1200, and 130 cal years BP, all coeval with known transitions between colder and warmer intervals of the Late Holocene, and regime shifts in the Pikialasorsuaq. Notably, a weaker/contracted polynya during the Roman Warm Period and Medieval Climate Anomaly caused the diatom community to reorganize via shifts in species composition, with the presence of larger taxa but lower diversity, and significantly reduced export production. This study underlines the high sensitivity of primary producers to changes in the polynya dynamics and illustrates that the strong pulse of early-spring cryopelagic diatoms that makes the Pikialasorsuaq exceptionally productive may be jeopardized by rapid warming and associated Nares Strait ice arch destabilization. Future alterations to the phenology of primary producers may disproportionately impact higher trophic levels and keystone species in this region, with implications for Indigenous Peoples and global diversity.  # Marine diatoms record Late Holocene regime shifts in the Pikialasorsuaq ecosystem [https://doi.org/10.5061/dryad.cz8w9gj8p](https://doi.org/10.5061/dryad.cz8w9gj8p) This dataset includes diatom counts (relative abundances, %) from core AMD15-Casq1. Diatoms were analyzed at a 1 to 10 cm sampling interval, which corresponds to an effective age resolution ranging from ca. 3 to 64 years (mean: 31 years). Absolute abundances are reported in valves per g of dry sediment. Fluxes were calculated by combining diatom concentrations (valves and spores g-1) with mass accumulation rates (g cm-2 yr-1). ## Description of the data and file structure Diatom data are presented against depth and modelled age (years BP) in the sediment archive. ## Sharing/Access information n/a ## Code/Software n/a

This dataset contains phenological records (timing of life events such as the opening of flowers) for tundra plant species from eight 2x2m monitoring plots. Plots are from two distinct vegetation communities (Herschel, Komakuk, coded in the data as HER and KOM). Plots were established in 2016 and monitored in 2016 and 2017. Data are presented as phenological stages for each monitored plant individual at survey dates across the 2016 and 2017 growing seasons. Flower stalk length, leaf length and new growth length were measured in mm. Active layer depth was measured in cm and was recorded at the corner of each 2x2 m plot. Soil moisture was measured as a percentage. Funding was provided by the NERC grant NE/M016323/1. Plots were visited on different dates across the 2016 and 2017 growing seasons. During each visit, the phenological stage of marked plant individuals was recorded. The lengths of the longest flower stalks and the longest leaves were measured during each visit. There were five monitored species - Salix arctica - SALARC Salix pulchra - SALPUL Eriophorum vaginatum - ERIVAG Dryas integrifolia - DRYINT Arctagrostis latifolia - ARCLAT There were two distinct vegetation communities - Herschel - HER Komakuk - KOM Flower stalk length, leaf length and new growth length were measured using digital callipers. A metal probe was used to measure active layer depth. Soil moisture was measured using an electronic soil moisture meter. Resolution: 2x2 meter plots Data collection methods were consistent across 2016 and 2017.

Dataset 1: Brain and body size Published measures of brain size (g) for 131 species of seabird. Brain size estimates were generated from the measurement of adult skulls in museum collections using the endocast method. For each species, multiple specimens were measured and a mean value was calculated to provide a single, species-specific brain size estimate. To account for the allometric relationship between brain and body size, we also obtained information on body size (g). Dataset 2: Natal and adult dispersal rates We collated data on natal and adult dispersal rates by conducting a systematic literature search using the online database, Web of Science. The literature search generated a total of 793 papers and reports and from these, we extracted natal and adult dispersal rates. Here, natal dispersal is defined as the annual proportion of fledglings recruiting into a colony different from their natal colony, and adult dispersal is defined as the annual proportion of adults relocating to a new breeding colony. The final dataset included dispersal estimates from 47 studies and 29 species. For studies that provided multiple dispersal rate estimates, i.e., for different adult age classes or for males and females (n=9), we calculated a species mean value. For this final list, we also collated information on age at first breeding and fledging time. We selected age at first breeding to reflect the species-specific time that is available to prospect different colonies, and fledging time to reflect maternal investment. Where multiple species-specific values were provided for age at first breeding, we calculated the mean weighted by the percentage of individuals that had bred by each age. Where a range was provided for fledging time, we took the midpoint. Dataset 3: Extinction risk and threats We extracted a species’ threat status from the IUCN Red List database (iucnredlist.org, 2020) and their vulnerability to six relevant anthropogenic threats listed under the Threats Classification Scheme (v. 3.3, IUCN, 2020). The six anthropogenic threats we considered were: climate change, biological resource use (e.g., fishing), human intrusions and disturbance, invasive species, energy production and mining, and pollution. Threat vulnerability was classified as: ‘vulnerable’ or ‘not vulnerable’. We used the IUCN classifications to group species into two broader categories of extinction risk. Here, species classified as Critically Endangered (CR), Endangered (E) and Vulnerable (V) were defined as ‘threatened’, and species listed as Near Threatened (NT) and Least Concern (LC) were defined as ‘non-threatened’. The cognitive buffer hypothesis proposes that species with larger brains (relative to their body size) exhibit greater behavioural flexibility, conferring an advantage in unpredictable or novel environments. Therefore, behavioural flexibility – and relative brain size – are likely to be important predictors of a species’ vulnerability to anthropogenic pressures and, ultimately, extinction risk. However, current evidence linking brain size to species vulnerability and extinction risk is inconclusive. Furthermore, studies examining the relationship between relative brain size and behavioural flexibility have mainly focused on foraging innovations, whilst other forms of behavioural flexibility remain unexplored. In this study, we collate species-specific information and examine links between relative brain size, rates of natal and adult dispersal (a measure of flexibility in breeding site fidelity), vulnerability to six anthropogenic threats and extinction risk for 131 species of seabird. We focused our study on seabirds, a highly threatened group that displays large variation in both relative brain size and dispersal behaviour. We found a significant positive relationship between relative brain size and natal dispersal rate, suggesting that relative brain size could enhance flexibility in breeding site choice in seabirds, consistent with the cognitive buffer hypothesis. However, this relationship does not persist when we consider adult dispersal, possibly reflecting constraints imposed by mate selection and knowledge transfer in seabirds. We also show that relative brain size is negatively associated with vulnerability to climate change. These findings have immediate application for predicting interspecific variation in species’ vulnerability to climate change and identifying priority species for conservation.

The Buxton Climate Change Impacts study was established in 1992 on a steep daleside of calcareous grassland outside Buxton, Derbyshire, UK. The vegetation has been surveyed annually since 1994 with nondestructive point quadrat touches (with gaps in 2005, 2007, and 2008) in early summer that correlate with total plot biomass. In five replicate blocks of 3 x 3 m plots, the vegetation has been subjected to climate treatments of winter heating (3C above ambient, Nov-April), summer drought (no rain, July-Aug), summer augmented rainfaill (20% above the long-term average, June-Sept), and two interaction treatments (heating-drought, heating-watered) in addition to replicated controls. The grassland is maintained in a short turf to simulate sheep and cattle grazing each autumn (Oct).

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MOHC.HadGEM3-GC31-MM.amip' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

This data package contains data used for an model-data intercomparison originally published in: D. K. Hutchinson, H. K. Coxall, D. J. Lunt, M. Steinthorsdottir, A. M. de Boer, M. Baatsen, A. von der Heydt, M. Huber, A. T. Kennedy-Asser, L. Kunzmann, J.-B. Ladant, C. H. Lear, K. Moraweck, P. N. Pearson, E. Piga, M. J. Pound, U. Salzmann, H. D. Scher, W. P. Sijp, K. K. Śliwińska, P. A. Wilson, and Z. Zhang, 2021: The Eocene-Oligocene transition: a review of marine and terrestrial proxy data, models and model-data comparisons, Climate of the Past, 17, 269-315. https://doi.org/10.5194/cp-17-269-2021 These data are also used in a further model-data intercomparison of Antarctic temperatures: Emily Tibbett, Natalie J Burls, David K. Hutchinson, Sarah J Feakins, (2023), Proxy-Model Comparison for the Eocene-Oligocene Transition in Southern High Latitudes, Paleoceanography and Paleocliamtology, In Review. Pre-print avaiable from: https://www.authorea.com/doi/full/10.1002/essoar.10511735.2 The package contains surface air temperature and sea surface temperature from an ensemble of model simulations of the Eocene-Oligocene transition. These data are provided at annual and monthly frequency. They are also provided on the original model grid, and an interpolated common grid used for the intercomparison. (The common grid is based on the HadCM3BL model grid.) All data are provided in NETCDF format with self-describing variable names. The name and explanation of the interpolated data files are contained in: table_of_experiments.xlsx Please read that spreadsheet to interpret the filenames, and see Table 2 (p291) of Hutchinson et al (2021) for experiment descriptions. Please also be mindful to cite the original authors of the simulations when using these data, whose work made this dataset possible. The appropriate citations are listed below: Reference DOI link Baatsen et al (2020) https://doi.org/10.5194/cp-16-2573-2020 Goldner et al (2014) https://doi.org/10.1038/nature13597 Ladant et al (2014a,b) https://doi.org/10.5194/cp-10-1957-2014 https://doi.org/10.1002/2013PA002593 Hutchinson et al (2018, 2019) https://doi.org/10.5194/cp-14-789-2018 https://doi.org/10.1038/s41467-019-11828-z Kennedy et al (2015) https://doi.org/10.1098/rsta.2014.0419 Zhang et al (2012, 2014) https://doi.org/10.5194/gmd-5-523-2012 https://doi.org/10.1038/nature13705 Sijp et al (2009) https://doi.org/10.1175/2009JCLI3003.1