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Associated data and R code for the paper Epstein & Roberts 2022 - Identifying priority areas to manage mobile bottom fishing on seabed carbon in the UK. This repository contains the primary output data from a desk-based investigation of seabed sediment organic carbon (OC) and mobile demeresal fishing in the UKEEZ. Best available published datasets were combined to produce unified maps of predicted seabed OC stocks, mean annual mobile bottom fishing disturbance, mean value of fish landed by mobile bottom fishing, and mean annual cummulative disturbance to seabed carbon from mobile bottom fishing. This data was combined with modeling of estimated fishing displacement to idenitfy priority areas for managmement and/or future research. For further methodological information please refer to the full paper published at PLOS Climate.

The survey was undertaken by a survey company commissioned by Plymouth Marine Laboratory (PML). The company obtained data through door-to-door surveys, inputting responses straight into custom-designed survey templates on a hand-held tablet platform. Data were subsequently collated in a password-protected excel spreadsheet and forwarded to the PML research team liaison point. Results of a survey undertaken in 2018 involving a range of open and closed questions intended to elicit local residents’ values they attach to the importance of coastal attributes and their perceptions of various tidal and wave energy development characteristics. Three case study sites were selected: Weston-super-Mare, Minehead, and the Taw-Torridge Estuary, South-West UK.

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).

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.

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

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

We utilize a variety of climate datasets to examine impacts of two mechanisms on precipitation in the Greater Horn of Africa (GHA) during northern-hemisphere summer. First, surface-pressure gradients draw moist air toward the GHA from the tropical Atlantic Ocean and Congo Basin. Variability of the strength of these gradients strongly influences GHA precipitation totals and accounts for important phenomena such as the 1960s–1980s rainfall decline and devastating 1984 drought. Following the 1980s, precipitation variability became increasingly influenced by the southern tropical Indian Ocean (STIO) region. Within this region, increases in sea-surface temperature, evaporation, and precipitation are linked with increased exports of dry mid-tropospheric air from the STIO region toward the GHA. Convergence of dry air above the GHA reduces local convection and precipitation. It also produces a clockwise circulation response near the ground that reduces moisture transports from the Congo Basin. Because precipitation originating in the Congo Basin has a unique isotopic signature, records of moisture transports from the Congo Basin may be preserved in the isotopic composition of annual tree rings in the Ethiopian Highlands. A negative trend in tree-ring oxygen-18 during the past half century suggests a decline in the proportion of precipitation originating from the Congo Basin. This trend may not be part of a natural cycle that will soon rebound because climate models characterize Indian Ocean warming as a principal signature of greenhouse-gas induced climate change. We therefore expect surface warming in the STIO region to continue to negatively impact GHA precipitation during northern-hemisphere summer.

Abstract In some shelf sea regions of the world, the tidal range is sufficient to convert the potential energy of the tides into electricity via tidal range power plants. As an island continent, Australia is one such region – a previous study estimated that Australia hosts up to 30% of the world’s resource. Here, we make use of a gridded tidal dataset (TPXO9) to characterize the tidal range resource of Australia. We examine the theoretical resource, and we also investigate the technical resource through 0D modelling with tidal range power plant operation. We find that the tidal range resource of Australia is 2004 TWh/yr, or about 22% of the global resource. This exceeds Australia’s total energy consumption for 2018/2019 (1721 TWh/yr), suggesting tidal range energy has the potential to make a substantial contribution to Australia’s electricity generation (265 TWh/yr in 2018/2019). Due to local resonance, the resource is concentrated in the sparsely populated Kimberley region of Western Australia. However, the tidal range resource in this region presents a renewable energy export opportunity, connecting to markets in southeast Asia. Combining the electricity from two complementary sites, with some degree of optimization tidal range schemes in this region can produce electricity for 45% of the year.