ALBERT

Description: The ability to adapt to social and environmental change is an increasingly critical feature of environmental governance. However, an understanding of how specific features of governance systems influence how they respond to change is still limited. Here we focus on how system features like diversity, heterogeneity, and connectedness impact stability, which indicates a system's capacity to recover from perturbations. Through a framework that combines agent-based modeling with "generalized"dynamical systems modeling, we model the stability of thousands of governance structures consisting of groups of resource users and non-government organizations interacting strategically with the decision centers that mediate their access to a shared resource. Stabilizing factors include greater effort dedicated to venue shopping and a greater fraction of non-government organizations in the system. Destabilizing factors include greater heterogeneity among actors, a greater diversity of decision centers, and greater interdependence between actors. The results suggest that while complexity tends to be destabilizing, there are mitigating factors that may help balance adaptivity and stability in complex governance. This study demonstrates the potential in applying the insights of complex systems theory to managing complex and highly uncertain human-natural systems in the face of rapid social and environmental change.

Description: Current questions in ecology revolve around instabilities in the dynamics on spatial networks and particularly the effect of node heterogeneity. We extend the master stability function formalism to inhomogeneous biregular networks having two types of spatial nodes. Notably, this class of systems also allows the investigation of certain types of dynamics on higher-order networks. Combined with the generalized modeling approach to study the linear stability of steady states, this is a powerful tool to numerically asses the stability of large ensembles of systems. We analyze the stability of ecological metacommunities with two distinct types of habitats analytically and numerically in order to identify several sets of conditions under which the dynamics can become stabilized by dispersal. Our analytical approach allows general insights into stabilizing and destabilizing effects in metapopulations. Specifically, we identify self-regulation and negative feedback loops between source and sink populations as stabilizing mechanisms and we show that maladaptive dispersal may be stable under certain conditions.

Description: portfolio available for a species to cope with and mitigate effects of climate change. Here, we quantified variation in larval survival and physiological rates of Carcinus maenas among populations occurring in distant or contrasting habitats (Cádiz: Spain, Helgoland: North Sea, Kerteminde: Baltic Sea). During the reproductive season, we reared larvae of these populations, in the laboratory, under a combination of several temperatures (15–24 °C) and salinities (25 and 32.5 PSU). In survival, all three populations showed a mitigating effect of high temperatures at lower salinity, with the strongest pattern for Helgoland. However, Cádiz and Kerteminde differed from Helgoland in that a strong thermal mitigation did not occur for growth and developmental rates. For all populations, oxygen consumption rates were driven only by temperature; hence, these could not explain the growth rate depression found at lower salinity. Larvae from Cádiz, reared in seawater, showed increased survival at the highest temperature, which differs from Helgoland (no clear survival pattern), and especially Kerteminde (decreased survival at high temperature). These responses from the Cádiz population correspond with the larval and parental habitat (i.e., high salinity and temperature) and may reflect local adaptation. Overall, along the European coast, C. maenas larvae showed a diversity of responses, which may enable specific populations to tolerate warming and subsidise more vulnerable populations. In such case, C. maenas would be able to cope with climate change through a spatial portfolio effect.

Description: Dataset: Temperature Loggers

Description: Temperature loggers (HOBO) placed in two locations (HOBO1: 10.74373, 124.78668, HOBO2: 10.74364, 124.78665) off the coast of the West coast of Leyte, the Philippines , 2012-2019. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/862415

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1430218

Description: Marine particles of different nature are found throughout the global ocean. The term "marine particles"describes detritus aggregates and fecal pellets as well as bacterioplankton, phytoplankton, zooplankton and nekton. Here, we present a global particle size distribution dataset obtained with several Underwater Vision Profiler 5 (UVP5) camera systems. Overall, within the 64 μm to about 50 mm size range covered by the UVP5, detrital particles are the most abundant component of all marine particles; thus, measurements of the particle size distribution with the UVP5 can yield important information on detrital particle dynamics. During deployment, which is possible down to 6000 m depth, the UVP5 images a volume of about 1 L at a frequency of 6 to 20 Hz. Each image is segmented in real time, and size measurements of particles are automatically stored. All UVP5 units used to generate the dataset presented here were inter-calibrated using a UVP5 high-definition unit as reference. Our consistent particle size distribution dataset contains 8805 vertical profiles collected between 19 June 2008 and 23 November 2020. All major ocean basins, as well as the Mediterranean Sea and the Baltic Sea, were sampled. A total of 19 % of all profiles had a maximum sampling depth shallower than 200 dbar, 38 % sampled at least the upper 1000 dbar depth range and 11 % went down to at least 3000 dbar depth. First analysis of the particle size distribution dataset shows that particle abundance is found to be high at high latitudes and in coastal areas where surface productivity or continental inputs are elevated. The lowest values are found in the deep ocean and in the oceanic gyres. Our dataset should be valuable for more in-depth studies that focus on the analysis of regional, temporal and global patterns of particle size distribution and flux as well as for the development and adjustment of regional and global biogeochemical models. The marine particle size distribution dataset is available at 10.1594/PANGAEA.924375.

Description: Dataset: RI Functional Trait Data

Description: This dataset represents an archive of the fish functional trait data in the Northeast Atlantic Ocean from fish sampled in the Rhode Island salt ponds from June to October 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/870857

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1652320

Description: 2023-01-01

Description: Dataset: BASIN 2019 Sediment properties

Description: Sediments were collected in Fall 2019 across three transects in the Santa Barbara Basin using the ROV Jason during R/V Atlantis cruise AT42-19. This dataset consists of the sediment parameters porosity and density. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/867113

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829981, NSF Division of Ocean Sciences (NSF OCE) OCE-1830033

Description: 2022-12-31

Description: Dataset: Acer Fecundity Gamete Bundles

Description: As a secondary assessment of fecundity, colonies of Acropora cerviconis (various genets) were taken to Mote Marine Laboratory in August 2020 for spawning and ex situ assisted sexual reproduction. From genets that spawned, forty random gamete bundles were collected during spawning and the total number of eggs and sperm per bundle were quantified. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/868493

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1452538

Description: 2022-12-31

Description: Dataset: BASIN 2019 Porewater geochemistry

Description: Sediments were collected in Fall 2019 across three transects in the Santa Barbara Basin using the ROV Jason during R/V Atlantis cruise AT42-19. Porewater was separated from the sediments and geochemical properties measured. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/867007

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829981, NSF Division of Ocean Sciences (NSF OCE) OCE-1830033

Description: 2022-12-31

Description: Dataset: BASIN 2019 Microbial activity

Description: Sediments were collected in Fall 2019 across three transects in the Santa Barbara Basin using the ROV Jason during R/V Atlantis cruise AT42-19. Microbial activity in the sediments was determined by measuring sulfate reduction rates. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/867221

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829981, NSF Division of Ocean Sciences (NSF OCE) OCE-1830033

Description: 2022-12-31

Description: Dataset: Acer Fecundity Polpys per Area

Description: Primary fecundity was assessed for Acropora cervicornis corals with known disease susceptibility. This dataset presents information on the number of polyps per area from linear branches of five colonies with 12 genets held in Mote Marine Lab’s spawning nurseries. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/868308

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1452538

Description: 2022-12-31

Description: Dataset: Acer Fecundity Oocyte Size

Description: Primary fecundity was assessed for Acropora cervicornis corals with known disease susceptibility. This dataset presents information on oocyte sizes from dissections of coral polyps from five adult colonies containing 12 genets held in Mote Marine Lab’s spawning nurseries. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/843067

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1452538

Description: 2022-12-31

Description: Dataset: Acropora hyacinthus ITS2 amplicon sequencing

Description: This dataset represents ITS2 amplicon sequences from Acropora hyacinthus samples collected at mutliple timepoints in Moorea, French Polynesia after the mass bleaching event of 2019. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/876564

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1935308, NSF Division of Ocean Sciences (NSF OCE) OCE-1935305

Description: 2022-12-31

Description: Dataset: Acer Fecundity Oocyte Number

Description: Primary fecundity was assessed for Acropora cervicornis corals with known disease susceptibility. This dataset presents oocyte numbers from dissections of coral polyps from five adult colonies from 12 genets held in Mote Marine Lab’s spawning nurseries. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/867314

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1452538

Description: 2022-12-31

Description: Dataset: ProteOMZ Exclusive Peptide Level Spectral Counts

Description: Relative protein abundance from scaled and corrected exclusive peptide spectral counts from 20-1250 m in the water column (0.2-3 µm filter size fraction) from the ProteOMZ R/V Falkor expedition. There are a total of 107,579 unique peptide sequences from 56,543 protein groups (88,251 proteins). Exclusive spectral counts are provided per sample as are the full dataset scaled and normalized spectral counts. The protein distributions in this dataset highlight the microbial dynamics across biomes in the central Pacific Ocean. These data were submitted in Saunders et al. (2022). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/868030

Description: Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, Schmidt Ocean Institute (SOI) R/V Falkor 160115 SOI ProteOMZ Expedition

Description: The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISSE2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

Description: Allometric relationships between body properties of animals are useful for a wide variety of purposes, such as estimation of biomass, growth, population structure, bioenergetic modelling and carbon flux studies. This study summarizes allometric relationships of zooplankton and nekton species that play major roles in polar marine food webs. Measurements were performed on 639 individuals of 15 species sampled during three expeditions in the Southern Ocean (winter and summer) and 2374 individuals of 14 species sampled during three expeditions in the Arctic Ocean (spring and summer). The information provided by this study fills current knowledge gaps on relationships between length and wet/dry mass of understudied animals, such as various gelatinous zooplankton, and of animals from understudied seasons and maturity stages, for example, for the krill Thysanoessa macrura and larval Euphausia superba caught in winter. Comparisons show that there is intra-specific variation in length–mass relationships of several species depending on season, e.g. for the amphipod Themisto libellula. To investigate the potential use of generalized regression models, comparisons between sexes, maturity stages or age classes were performed and are discussed, such as for the several krill species and T. libellula. Regression model comparisons on age classes of the fish E. antarctica were inconclusive about their general use. Other allometric measurements performed on carapaces, eyes, heads, telsons, tails and otoliths provided models that proved to be useful for estimating length or mass in, e.g. diet studies. In some cases, the suitability of these models may depend on species or developmental stages.

Description: N.N. Ambraseys left us a wealth of papers and volumes on a number of topics; many of them concern the historical earth- quake investigation. One of the last works is the 2009 volume (Ambraseys in Earthquakes in the Eastern Mediterranean and the Middle East: a multidisciplinary study of 2000 years of seismicity, Cambridge, Cambridge, UK, 2009), where he summarizes the results of more than thirty years of investigation through archives and libraries, covering earthquakes of a large area, from Albania to Caucasus. For each earthquake, a short summary of the main effects is supplied, together with the list of the sources used. Such information is intended as material for assessing location and size of the earthquakes, task that the author accomplished only in a very preliminary way for a few earthquakes, only. In addition to exhaustive descriptions of the most known earthquakes and the relevant historical sources, the volume contains information on a large number of earthquakes, so far unknown to the current earthquake catalogues. This paper intends to represent a homage to his immense work, partially showing the potential of his volume. We briefly present here some case histories, including the preliminary location and size of the earthquakes – known and unknown—around Anatolia. We add some examples of how he was able to prove that some alleged earthquakes are actually to be considered as fake or very doubtful. We also present the damage information supplied for some known and unknown earthquakes, and how they can be used for assessing location and size of them.

Description: Published

Description: 555–568

Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica

Description: N/A or not JCR

Description: This study develops a new spatial correlation model for Italy using the most up-to-date and densest dataset of accelerometer and velocimeter records available. The objective is to estimate the average correlation length and assess its impact on the prediction accuracy of the Italian Shakemap compared to the global model (Loth and Baker, 2013–LB13) adopted in the default configuration of the program. We compute the spatial covariance structure using a geostatistical approach based on traditional variography applied to standardized residuals within the events of a reference ground motion model (ITA10). We observe spatial clusters of the correlation lengths and a wide variability over the Italian territory linked to the profound heterogeneity of the geological and geomorphological context. The obtained estimates are then implemented within the LB13 co-regionalization model in place of the default values while assuming the same cross-correlation coefficients among spectral parameters. Although our results are quite consistent with previous models calibrated for Italy, we find that the inclusion of the new correlation lengths in the Shakemap predictions, assessed through a leave-one-out cross-validation technique, results in a non-appreciable improvement over the global model, thus indicating that the adopted approach is not able to resolve the regional features and the corresponding spatial correlation with reference to individual scenarios. These findings may suggest the need to move towards nonergodic models in the Shakemap computing to better capture the spatial variability or to determine different co-regionalisation matrices more suitable for the regional applications.

Description: Published

Description: 1847–1873

Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica

Description: JCR Journal

Description: Natural gas hazard was assessed at Cava dei Selci, a residential neighbourhood of Marino (Rome) by a joint study of gas emissions and related health problems. Here a densely urbanized zone with 4000 residents surrounds a dangerous natural gas discharge where, along the years, dozens of animals were killed by the gas. Gas originates from Colli Albani volcano and consists mostly of CO2 with ~1 vol.% of H2S. In recent years, several gas-related accidents occurred in the urbanized zone (gas blowouts and road collapses). Some houses were evacuated because of hazardous indoor air gas concentration. Gas hazard was assessed by soil CO2 flux and concentration surveys and indoor and outdoor air CO2 and H2S concentration measurements. Open fields and house gardens release a high quantity of CO2 (32.23 tonnes*day-1). Inside most houses, CO2 air concentration exceeds 0.1 vol.%, the acceptable long-term exposure range. In several houses both CO2 and H2S exceed the IDLH level (Immediately Dangerous to Life and Health). An epidemiological cohort study was carried out on the residents of two Cava dei Selci zones with high (ZoneA) and medium (ZoneB) gas hazard exposure, using the rest of Marino as reference zone. We found excess mortality and Emergency Room Visits (ERV) related to high exposure to CO2 and H2S; in particular , an increased risk of mortality and ERV for diseases of central nervous system (HR 1.57, 95% CI 0.76-3.25 and HR 5.82, 95% CI 1.27-26.56 respectively) was found among men living in Zone A.

Description: Published

Description: 707–729

Description: 6A. Geochimica per l'ambiente e geologia medica

Description: JCR Journal

Description: Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar – SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015–2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle () with a high topographic wetness index (TWI) (〉7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.

Description: Despite global warming and Arctic sea-ice loss, on average the Antarctic sea-ice extent has not declined since 1979 when satellite data became available. In contrast, climate model simulations tend to exhibit strong negative sea-ice trends for the same period. This Antarctic sea-ice paradox leads to low confidence in 21st-century sea-ice projections. Here we present multi-resolution climate change projections that account for Southern Ocean mesoscale eddies. The high-resolution configuration simulates stable September Antarctic sea-ice extent that is not projected to decline until the mid-21st century. We argue that one reason for this finding is a more realistic ocean circulation that increases the equatorward heat transport response to global warming. As a result, the ocean becomes more efficient at moderating the anthropogenic warming around Antarctica and hence at delaying sea-ice decline. Our study suggests that explicitly simulating Southern Ocean eddies is necessary for providing Antarctic sea-ice projections with higher confidence.

Description: Our understanding of the biogeochemical cycling of the climate-relevant trace gas dimethyl sulfide (DMS) in the Peruvian upwelling system is still limited. Here we present oceanic and atmospheric DMS measurements which were made during two shipborne cruises in December 2012 (M91) and October 2015 (SO243) in the Peruvian upwelling region. Dimethylsulfoniopropionate (DMSP) and dimethyl sulfoxide (DMSO) were also measured during M91. DMS concentrations were 1.9 ± 0.9 and 2.5 ± 1.9 nmol L−1 in surface waters in October 2015 and December 2012, respectively. Nutrient availability appeared to be the main driver of the observed variability in the surface DMS distributions in the coastal areas. DMS, DMSP, and DMSO showed maxima in the surface layer, and no elevated concentrations associated with the oxygen minimum zone off Peru were measured. The possible role of DMS, DMSP, and DMSO as radical scavengers (stimulated by nitrogen limitation) is supported by their negative correlations with N:P (sum of nitrate and nitrite : dissolved phosphate) ratios. Large variations in atmospheric DMS mole fractions were measured during M91 (144.6 ± 95.0 ppt) and SO243 (91.4 ± 55.8 ppt); however, the atmospheric mole fractions were generally low, and the sea-to-air flux was primarily driven by seawater DMS. The Peruvian upwelling region was identified as a source of atmospheric DMS in December 2012 and October 2015. However, in comparison to the previous measurements in the adjacent regions, the Peru upwelling was a moderate source of DMS emissions at either time (M91: 5.9 ± 5.3 µmol m−2 d−1; SO243: 3.8 ± 2.7 µmol m−2 d−1).

Description: Most earth system models (ESMs) neglect climate feedbacks arising from carbon release from thawing permafrost, especially from thawing of subsea permafrost (SSPF). To assess the fate of SSPF in the next 1000 years, we implemented SSPF into JSBACH, the land component of the Max Planck Institute Earth System Model (MPI-ESM). This is the first implementation of SSPF processes in an ESM component. We investigate three extended scenarios from the 6th phase of the Coupled Model Intercomparison Project (CMIP6). In the 21st century only small differences are found among the scenarios, but in the upper-end emission scenario SSP5-8.5 (shared socio-economic pathway), especially in the 22nd century, SSPF ice melting is more than 15 times faster than in the pre-industrial period. In this scenario about 35ĝ% of total SSPF volume and 34ĝ% of SSPF area are lost by the year 3000 due to climatic changes. In the more moderate scenarios, the melting rate maximally exceeds that of pre-industrial times by a factor of 4, and the climate change induced SSPF loss (volume and area) by the year 3000 does not exceed 14ĝ%. Our results suggest that the rate of melting of SSPF ice is related to the length of the local open-water season and thus that the easily observable sea ice concentration may be used as a proxy for the change in SSPF.

Description: Measurements targeting mesoscale and smaller-scale processes in the ice-covered part of the Arctic Ocean are sparse in all seasons. As a result, there are significant knowledge gaps with respect to these processes, particularly related to the role of eddies and fronts in the coupled ocean-atmosphere-sea ice system. Here we present a unique observational dataset of upper ocean temperature and salinity collected by a set of buoys installed on ice floes as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network. The multi-sensor systems, each equipped with five temperature and salinity recorders on a 100 m long inductive modem tether, drifted together with the main MOSAiC ice camp through the Arctic Transpolar Drift between October 2019 and August 2020. They transmitted hydrographic in situ data via the iridium satellite network at 10 min intervals. While three buoys failed early due to ice dynamics, five of them recorded data continuously for 10 months. A total of four units were successfully recovered in early August 2020, additionally yielding internally stored instrument data at 2 min intervals. The raw data were merged, processed, quality controlled, and validated using independent measurements also obtained during MOSAiC. Compilations of the raw and processed datasets are publicly available at 10.1594/PANGAEA.937271 and 10.1594/PANGAEA.940320 , respectively. As an important part of the MOSAiC physical oceanography program, this unique dataset has many synergies with the manifold co-located observational datasets and is expected to yield significant insights into ocean processes and to contribute to the validation of high-resolution numerical simulations. While this dataset has the potential to contribute to submesoscale process studies, this paper mainly highlights selected preliminary findings on mesoscale processes.

Description: The EPICA Dome C (EDC) ice core provides the longest continuous climatic record, covering the last 800 000 years (800 kyr). A unique opportunity to investigate decadal to millennial variability during past glacial and interglacial periods is provided by the high-resolution water isotopic record (δ18O and δD) available for the EDC ice core. We present here a continuous compilation of the EDC water isotopic record at a sample resolution of 11 cm, which consists of 27000 δ18O measurements and 7920 δD measurements (covering, respectively, 94 % and 27 % of the whole EDC record), including published and new measurements (2900 for both δ18O and δD) for the last 800kyr. Here, we demonstrate that repeated water isotope measurements of the same EDC samples from different depth intervals obtained using different analytical methods are comparable within analytical uncertainty. We thus combine all available EDC water isotope measurements to generate a high-resolution (11 cm) dataset for the past 800 kyr. A frequency decomposition of the most complete δ18O record and a simple assessment of the possible influence of diffusion on the measured profile shows that the variability at the multidecadal to multi-centennial timescale is higher during glacial than during interglacial periods and higher during early interglacial isotopic maxima than during the Holocene. This analysis shows as well that during interglacial periods characterized by a temperature optimum at the beginning, the multi-centennial variability is strongest over this temperature optimum.

Description: Here we describe the LegacyPollen 1.0, a dataset of 2831 fossil pollen records with metadata, a harmonized taxonomy, and standardized chronologies. A total of 1032 records originate from North America, 1075 from Europe, 488 from Asia, 150 from Latin America, 54 from Africa, and 32 from the Indo-Pacific. The pollen data cover the late Quaternary (mostly the Holocene). The original 10 110 pollen taxa names (including variations in the notations) were harmonized to 1002 terrestrial taxa (including Cyperaceae), with woody taxa and major herbaceous taxa harmonized to genus level and other herbaceous taxa to family level. The dataset is valuable for synthesis studies of, for example, taxa areal changes, vegetation dynamics, human impacts (e.g., deforestation), and climate change at global or continental scales. The harmonized pollen and metadata as well as the harmonization table are available from PANGAEA (10.1594/PANGAEA.929773; Herzschuh et al., 2021). R code for the harmonization is provided at Zenodo (10.5281/zenodo.5910972; Herzschuh et al., 2022) so that datasets at a customized harmonization level can be easily established.

Description: We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats. All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection. The most common control points for the chronologies are radiocarbon dates (86.1ĝ€¯%), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials). The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8ĝ€¯% of records), reservoir effect (4.9ĝ€¯%), and sediment deposition discontinuity (4.4ĝ€¯%). Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4ĝ€¯% of records could be improved according to our assessment. Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change. The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is open-access and available at PANGAEA (10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (10.5281/zenodo.5815192; Li et al., 2022), respectively.

Description: We compile a data set of forest surveys from expeditions to the northeast of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia), and the Chukotka Autonomous Okrug (59-73°N, 97-169°E), performed between the years 2011 and 2021. The region is characterized by permafrost soils and forests dominated by larch (Larix gmelinii Rupr. and Larix cajanderi Mayr). Our data set consists of a plot database describing 226 georeferenced vegetation survey plots and a tree database with information about all the trees on these plots. The tree database, consisting of two tables with the same column names, contains information on the height, species, and vitality of 40289 trees. A subset of the trees was subject to a more detailed inventory, which recorded the stem diameter at base and at breast height, crown diameter, and height of the beginning of the crown. We recorded heights up to 28.5m (median 2.5m) and stand densities up to 120000 trees per hectare (median 1197ha-1), with both values tending to be higher in the more southerly areas. Observed taxa include Larix Mill., Pinus L., Picea A. Dietr., Abies Mill., Salix L., Betula L., Populus L., Alnus Mill., and Ulmus L. In this study, we present the forest inventory data aggregated per plot. Additionally, we connect the data with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of 10 species groups, allometries depended also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here. The data can be used for studying the forest structure of northeastern Siberia and for the calibration and validation of remotely sensed data. They are available at https://doi.org/10.1594/PANGAEA.943547 .