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Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

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

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.IPSL.IPSL-CM6A-LR.piControl' 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 IPSL-CM6A-LR climate model, released in 2017, includes the following components: atmos: LMDZ (NPv6, N96; 144 x 143 longitude/latitude; 79 levels; top level 80000 m), land: ORCHIDEE (v2.0, Water/Carbon/Energy mode), ocean: NEMO-OPA (eORCA1.3, tripolar primarily 1deg; 362 x 332 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: NEMO-PISCES, seaIce: NEMO-LIM3. The model was run by the Institut Pierre Simon Laplace, Paris 75252, France (IPSL) in native nominal resolutions: 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.HighResMIP.CNRM-CERFACS.CNRM-CM6-1-HR.hist-1950' 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 CNRM-CM6-1-HR climate model, released in 2017, includes the following components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T359; Gaussian Reduced with 181724 grid points in total distributed over 360 latitude circles (with 720 grid points per latitude circle between 32.2degN and 32.2degS reducing to 18 grid points per latitude circle at 89.6degN and 89.6degS); 91 levels; top level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA025, tripolar primarily 1/4deg; 1442 x 1050 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 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.INM.INM-CM4-8.ssp585' 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 INM-CM4-8 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 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

The impacts of increasing natural climate disasters are threatening food security in the Asia-Pacific region. Rice is Asia’s most important staple food. Climate variability and change directly impact rice production, through changes in rainfall, temperature and CO2 concentrations. The key for sustainable rice crop is water management. Adaptation can occur through shifts of cropping to higher latitudes and can profit from river systems (via irrigation) so far not considered. New opportunities arise to produce more than one crop per year in cooler areas. Asian wheat production in 2005 represents about 43 % of the global total. Changes in agronomic practices, such as earlier plant dates and cultivar substitution will be required. Fisheries play a crucial role in providing food security with the contribution of fish to dietary animal protein being very high in the region – up to 90 % in small island developing states (SIDS). With the warming of the Pacific and Indian Oceans and increased acidification, marine ecosystems are presently under stress. Despite these trends, maintaining or enhancing food production from the sea is critical. However, future sustainability must be maintained whilst also securing biodiversity conservation. Improved fisheries management to address the existing non-climate threats remains paramount in the Indian and Pacific Oceans with sustainable management regimes being established. Climate-related impacts are expected to increase in magnitude over the coming decades, thus preliminary adaptation to climate change is valuable.

Predicting likely species responses to an alteration of their local environment is key to decision‐making in resource management, ecosystem restoration and biodiversity conservation practice in the face of global human‐induced habitat disturbance. This is especially true for forest trees which are a dominant life form on Earth and play a central role in supporting diverse communities and structuring a wide range of ecosystems. In Europe, it is expected that most forest tree species will not be able to migrate North fast enough to follow the estimated temperature isocline shift given current predictions for rapid climate warming. In this context, a topical question for forest genetics research is to quantify the ability for tree species to adapt locally to strongly altered environmental conditions (Kremer et al. ). Identifying environmental factors driving local adaptation is, however, a major challenge for evolutionary biology and ecology in general but is particularly difficult in trees given their large individual and population size and long generation time. Empirical evaluation of local adaptation in trees has traditionally relied on fastidious long‐term common garden experiments (provenance trials) now supplemented by reference genome sequence analysis for a handful of economically valuable species. However, such resources have been lacking for most tree species despite their ecological importance in supporting whole ecosystems. In this issue of Molecular Ecology, De Kort et al. () provide original and convincing empirical evidence of local adaptation to temperature in black alder, Alnus glutinosa L. Gaertn, a surprisingly understudied keystone species supporting riparian ecosystems. Here, De Kort et al. () use an innovative empirical approach complementing state‐of‐the‐art landscape genomics analysis of A. glutinosa populations sampled in natura across a regional climate gradient with phenotypic trait assessment in a common garden experiment (Fig. ). By combining the two methods, De Kort et al. () were able to detect unequivocal association between temperature and phenotypic traits such as leaf size as well as with genetic loci putatively under divergent selection for temperature. The research by De Kort et al. () provides valuable insight into adaptive response to temperature variation for an ecologically important species and demonstrates the usefulness of an integrated approach for empirical evaluation of local adaptation in nonmodel species (Sork et al. ).