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As part of global efforts to reduce dependence on carbon-based energy sources there has been a rapid increase in the installation of renewable energy devices. The installation and operation of these devices can result in conflicts with wildlife. In the marine environment, mammals may avoid wind farms that are under construction or operating. Such avoidance may lead to more time spent travelling or displacement from key habitats. A paucity of data on at-sea movements of marine mammals around wind farms limits our understanding of the nature of their potential impacts. Here, we present the results of a telemetry study on harbour seals Phoca vitulina in The Wash, south-east England, an area where wind farms are being constructed using impact pile driving. We investigated whether seals avoid wind farms during operation, construction in its entirety, or during piling activity. The study was carried out using historical telemetry data collected prior to any wind farm development and telemetry data collected in 2012 during the construction of one wind farm and the operation of another. Within an operational wind farm, there was a close-to-significant increase in seal usage compared to prior to wind farm development. However, the wind farm was at the edge of a large area of increased usage, so the presence of the wind farm was unlikely to be the cause. There was no significant displacement during construction as a whole. However, during piling, seal usage (abundance) was significantly reduced up to 25 km from the piling activity; within 25 km of the centre of the wind farm, there was a 19 to 83% (95% confidence intervals) decrease in usage compared to during breaks in piling, equating to a mean estimated displacement of 440 individuals. This amounts to significant displacement starting from predicted received levels of between 166 and 178 dB re 1 μPa(p-p). Displacement was limited to piling activity; within 2 h of cessation of pile driving, seals were distributed as per the non-piling scenario. Synthesis and applications. Our spatial and temporal quantification of avoidance of wind farms by harbour seals is critical to reduce uncertainty and increase robustness in environmental impact assessments of future developments. Specifically, the results will allow policymakers to produce industry guidance on the likelihood of displacement of seals in response to pile driving; the relationship between sound levels and avoidance rates; and the duration of any avoidance, thus allowing far more accurate environmental assessments to be carried out during the consenting process. Further, our results can be used to inform mitigation strategies in terms of both the sound levels likely to cause displacement and what temporal patterns of piling would minimize the magnitude of the energetic impacts of displacement. Wash_diagWash_diag.xlsx is the historic location data (pre windfarm construction) for the 19 individuals used in the analysis described in Russell et al.

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

Anthropogenic structures (e.g. weirs and dams) fragment river networks and restrict the movement of migratory fish. Poor understanding of behavioural response to hydrodynamic cues at structures currently limits the development of effective barrier mitigation measures. This study aimed to assess the effect of flow constriction and associated flow patterns on eel behaviour during downstream migration. In a field experiment, we tracked the movements of 40 tagged adult European eels (Anguilla anguilla) through the forebay of a redundant hydropower intake under two manipulated hydrodynamic treatments. Interrogation of fish trajectories in relation to measured and modelled water velocities provided new insights into behaviour, fundamental for developing passage technologies for this endangered species. Eels rarely followed direct routes through the site. Initially, fish aligned with streamlines near the channel banks and approached the intake semi-passively. A switch to more energetically costly avoidance behaviours occurred on encountering constricted flow, prior to physical contact with structures. Under high water velocity gradients, fish then tended to escape rapidly back upstream, whereas exploratory ‘search’ behaviour was common when acceleration was low. This study highlights the importance of hydrodynamics in informing eel behaviour. This offers potential to develop behavioural guidance, improve fish passage solutions and enhance traditional physical screening. Fish_detections_UL_CHFish positions derived from acoustic telemetry contained within excel file with 5 columns. 'Record' denotes tag detection numbered consecutively in sequence; 'tag_number' denotes the fish identification number; ‘PosX’ denotes fish x coordinate in UTM; ‘PosY’ denotes fish y coordinate in UTM, ‘Treatment’ denotes experimental treatment

The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

Project: IPCC Data Distribution Centre : Supplementary data sets for the Sixth Assessment Report - For the Sixth Assessment Report of the IPCC (AR6) input/source and intermediate datasets underlying the AR6 were collected and long-term archived. This project compliments CMIP6 data subset and snapshot analyzed for the WGI AR6. Summary: This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox'. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

# Data from: Blue Carbon Benefits from Global Saltmarsh Restoration [https://doi.org/10.5061/dryad.pc866t1vp](https://doi.org/10.5061/dryad.pc866t1vp) This README file was generated on 12th September 2023 by Victoria Mason. **Title of Dataset:** Blue carbon benefits from global saltmarsh restoration. **Author information:** * Victoria G. Mason, Bangor University/Royal Netherlands Institute for Sea Research (NIOZ), victoria.mason@nioz.nl (*Corresponding author*) * Annette Burden, UK Centre for Ecology & Hydrology * Graham Epstein, University of Exeter/University of Victoria * Lucy L. Jupe, Wildfowl & Wetlands Trust * Kevin A. Wood, Wildfowl & Wetlands Trust * Martin W. Skov, Bangor University **Summary of dataset:** These data include all data which were extracted or derived from relevant studies on global saltmarsh carbon storage and greenhouse gas flux. Data were obtained following screening of 29,182 peer reviewed published studies for relevant data, which were then extracted from 431 studies via text, tables and figures. We then used a meta-analysis to assess drivers of variation in global saltmarsh and greenhouse gas flux. * Date of literature search: 21st January 2022. * Date of data extraction: February - March 2022 * Literature search conducted via: Scopus + Web of Science ## Description of the data and file structure The contents of these data include: * **Full dataset (Aug2023\_GlobalCarbonReview\_FullDataset.xls):** All data extracted from 431 relevant studies and used in analysis. This includes a title page, metadata (with descriptions of column headers) and the full dataset. Response variables included: * Carbon stock * Percentage organic carbon * Bulk density * Sediment accretion rate * Carbon accumulation rate * Carbon dioxide flux * Methane flux * Nitrous oxide flux **\- Data on each included study \(Aug2023\_GlobalCarbonReview\_IncludedStudies\.xls\):** List of each study included in the final analysis, and its metadata. This includes a title page, metadata (with descriptions of column headers) and the dataset. All data include standard deviation (SD) and n (number of replicates) where provided by the original study, which were used to calculate Hedge's *g* effect sizes reported in the subsequent study. | Frequently used abbreviations: | | | ------------------------------ | --- | | C | carbon | | OC | organic carbon | | GHG | greenhouse gas | | bd | bulk density (g cm-3 dry sediment) | | Y/N | yes/no | | ref | reference | | lat | latitude | | long | longitude | | rest | restoration | | prec | precipitation | | sal | salinity | | acc | accretion | | resp | respiration | | SR | soil respiration (appears for CO2 flux) | | ER | ecosystem respiration (appears for CO2 flux) | | n | number of samples included in mean/standard deviation | | sd | standard deviation | All abbreviations used are outlined in the ‘Metadata’ worksheet of .xls files. **Data specific information for Aug2023\_GlobalCarbonReview\_FullDataset.xls:** Number of variables: 88 Number of cases/rows: 2055 Variables included: See 'Metadata' sheet **Data specific information for** **Aug2023\_GlobalCarbonReview\_IncludedStudies.xls:** Number of variables: 47 Number of cases/rows: 431 Variables included: See 'Metadata' sheet **Empty cells:** Cells are empty where data on that variable were not provided by the original study from which they were extracted. For example, where a study provided data on carbon stock variables, but not greenhouse gas flux. For further details, see the 'Metadata' sheets of each file. ## Sharing/Access information These data are available via Dryad, and described in ‘Blue Carbon Benefits from Global Saltmarsh Restoration’, in Global Change Biology. **DOI:** 10.1111/gcb.16943 Data were extracted from 431 published peer reviewed articles, the details of which can be found in the attached datasheets. Coastal saltmarshes are found globally, yet are 25–50% reduced compared to their historical cover. Restoration is incentivised by the promise that marshes are efficient storers of ‘blue’ carbon, although the claim lacks substantiation across global contexts. We synthesised data from 431 studies to quantify the benefits of saltmarsh restoration to carbon accumulation and greenhouse gas uptake. The results showed global marshes store approximately 1.41–2.44 Pg carbon. Restored marshes had very low greenhouse gas (GHG) fluxes and rapid carbon accumulation, resulting in a mean net accumulation rate of 64.70 t CO2e ha-1 y-1. Using this estimate and potential restoration rates, we find saltmarsh regeneration could result in 12.93–207.03 Mt CO2e accumulation per year, offsetting the equivalent of up to 0.51% global-energy-related CO2 emissions – a substantial amount, considering marshes represent <1% of Earth’s surface. Carbon accumulation rates and GHG fluxes varied contextually with temperature, rainfall and dominant vegetation, with the eastern costs of the USA and Australia being particular hotspots for carbon storage. Whilst the study reveals paucity of data for some variables and continents, suggesting a need for further research, the potential for saltmarsh restoration to offset carbon emissions is clear. The ability to facilitate natural carbon accumulation by saltmarshes now rests principally on the action of the management-policy community and on financial opportunities for supporting restoration.

The ERC-funded FRAGSUS Project (Fragility and sustainability in small island environments: adaptation, cultural change and collapse in prehistory, 2013–18), led by Caroline Malone (Queens University Belfast) has explored issues of environmental fragility and Neolithic social resilience and sustainability during the Holocene period in the Maltese Islands. This, the first volume of three, presents the palaeo-environmental story of early Maltese landscapes. The project employed a programme of high-resolution chronological and stratigraphic investigations of the valley systems on Malta and Gozo. Buried deposits extracted through coring and geoarchaeological study yielded rich and chronologically controlled data that allow an important new understanding of environmental change in the islands. The study combined AMS radiocarbon and OSL chronologies with detailed palynological, molluscan and geoarchaeological analyses. These enable environmental reconstruction of prehistoric landscapes and the changing resources exploited by the islanders between the seventh and second millennia bc. The interdisciplinary studies combined with excavated economic and environmental materials from archaeological sites allows Temple landscapes to examine the dramatic and damaging impacts made by the first farming communities on the islands’ soil and resources. The project reveals the remarkable resilience of the soil-vegetational system of the island landscapes, as well as the adaptations made by Neolithic communities to harness their productivity, in the face of climatic change and inexorable soil erosion. Neolithic people evidently understood how to maintain soil fertility and cope with the inherently unstable changing landscapes of Malta. In contrast, second millennium bc Bronze Age societies failed to adapt effectively to the long-term aridifying trend so clearly highlighted in the soil and vegetation record. This failure led to severe and irreversible erosion and very different and short-lived socio-economic systems across the Maltese islands.

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage strengths of individual data types while statistically accounting for limitations, such as sampling biases.  Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned >