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  • Wiley  (1,037,736)
  • Wiley-Blackwell  (471,889)
  • PANGAEA  (423,575)
  • American Association for the Advancement of Science  (369,592)
  • Nature Publishing Group  (363,433)
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  • 1
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    Crustal uplift rates implied by synchronously investigating Late Quaternary marine terraces in the Milazzo Peninsula, Northeast Sicily, Italy (2024)
    Wiley
    Details
    Publication Date: 2024-07-09
    Description: Late Quaternary crustal uplift is well recognized in northeast Sicily, southern Italy, a region also prone to damaging earthquakes such as the 1908 “Messina” earthquake (Mw 7.1), the deadliest seismic event reported within the Italian Earthquake Catalogue. Yet it is still understudied if, within the Milazzo Peninsula, crustal uplift rates are varying spatially and temporally and whether they may be either influenced by (i) local upper-plate faulting activity or (ii) deep geodynamic processes. To investigate the long-term crustal vertical movements in northeast Sicily, we have mapped a flight of Middle-Late Pleistocene marine terraces within the Milazzo Peninsula and in its southern area and refined their chronology, using a synchronous correlation approach driven by published age controls. This has allowed a new calculation of the associated crustal uplift rates, along a north–south oriented coastal-parallel transect within the investigated area. Our results show a decreasing uplift rate from south to north across the Milazzo Peninsula and beyond, and that the associated rates of uplift have been constant through the Late Quaternary. This spatially varying yet temporally constant vertical deformation helps to constrain the amount of uplift, allowing us to explore which is the driving mechanism(s), proposing a few related scenarios. We discuss our results in terms of tectonic implications and emphasize the importance of using appropriate approaches, as such applying a synchronous correlation method, to refine chronologies of undated palaeoshorelines when used for tectonic investigations.
    Description: In press
    Description: OST2 Deformazione e Hazard sismico e da maremoto
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
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    Ensemble modelling to predict the distribution of vulnerable marine ecosystems indicator taxa on data‐limited seamounts of Cabo Verde (NW Africa) (2024)
    Wiley
    Details
    Publication Date: 2024-07-09
    Description: Aim Seamounts are conspicuous geological features with an important ecological role and can be considered vulnerable marine ecosystems (VMEs). Since many deep‐sea regions remain largely unexplored, investigating the occurrence of VME taxa on seamounts is challenging. Our study aimed to predict the distribution of four cold‐water coral (CWC) taxa, indicators for VMEs, in a region where occurrence data are scarce. Location Seamounts around the Cabo Verde archipelago (NW Africa). Methods We used species presence–absence data obtained from remotely operated vehicle (ROV) footage collected during two research expeditions. Terrain variables calculated using a multiscale approach from a 100‐m‐resolution bathymetry grid, as well as physical oceanographical data from the VIKING20X model, at a native resolution of 1/20°, were used as environmental predictors. Two modelling techniques (generalized additive model and random forest) were employed and single‐model predictions were combined into a final weighted‐average ensemble model. Model performance was validated using different metrics through cross‐validation. Results Terrain orientation, at broad scale, presented one of the highest relative variable contributions to the distribution models of all CWC taxa, suggesting that hydrodynamic–topographic interactions on the seamounts could benefit CWCs by maximizing food supply. However, changes at finer scales in terrain morphology and bottom salinity were important for driving differences in the distribution of specific CWCs. The ensemble model predicted the presence of VME taxa on all seamounts and consistently achieved the highest performance metrics, outperforming individual models. Nonetheless, model extrapolation and uncertainty, measured as the coefficient of variation, were high, particularly, in least surveyed areas across seamounts, highlighting the need to collect more data in future surveys. Main Conclusions Our study shows how data‐poor areas may be assessed for the likelihood of VMEs and provides important information to guide future research in Cabo Verde, which is fundamental to advise ongoing conservation planning.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 3
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    Integrated Geophysical‐Petrological 3D‐Modeling of the West and Central African Rift System and Its Adjoining Areas (2024)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-07-09
    Description: This study addresses the lithospheric structure of the West and Central African rift system (WCARS) and explores its origin and development in relation to the enigmatic Cameroon volcanic line (CVL). Based on a recent seismic tomography model, we subdivide the areas in tectonic domains. We perform integrated 3D geophysical and petrological forward modeling. By exploring the thickness and composition of different domains, we compare the model response to the observed topography and gravity anomalies, under consideration of the available seismic Moho depth points. Our model reveals three distinct domains within the study area: The WCARS is predominantly underlain by a Phanerozoic‐type lithospheric mantle, surrounded by the West African and the Congo Cratons, where the lithospheric mantle has a Proterozoic‐type signature. Between these domains, we identify a transition area where lithospheric thickness changes rapidly. Our preferred model shows significant variability of crustal thickness from 20 km in the rift area to 50 km beneath the cratons accompanied by thin lithosphere of 80 km in the rift area to thick lithosphere of up to 240 km beneath the cratons. The final model confirms that the WCARS' origin is passive, and suggests that the origin of the CVL, particularly its continental part, is the result of two tectonic events: (a) V‐shaped opening of the lithospheric mantle beneath the WCARS, resulting in (b) a strong variation of the lithosphere thickness at the transition between the rift zone and the northwestern part of the Congo craton. Plain Language Summary In this study, we describe the current structure of the subsurface (from the surface to a depth of 300 km) in Central and Western Africa. The aim is to understand the formation of the Central African Rift zone during the opening of the Atlantic Ocean, and how this relates to the linear chain of volcanoes that cross Cameroon, known as the Cameroon Volcanic Line. To achieve these objectives, we divide the study area into tectonic domains reflecting their seismological signature, and then, establish a three‐dimensional representation of the subsurface structure, based on fitting topography and gravity data. Our model confirms the geological subdivision of the study area into three blocks corresponding to two cratons and a rift zone, with transitional areas between them. Our model is compatible with a passive origin of the rifts in the region. We propose that the origin of the volcanic line of Cameroon is related to magma ascent during the separation of the African and South American plate in connection with the opening of the Atlantic and channeled by the lithospheric architecture. Key Points We present a new 3D model of the lithosphere for the West and Central African Rift System (WCARS) Our model confirms that the WCARS has a passive origin Our model suggest that the origin of the Cameroon volcanic line is linked to the architecture of the WCARS and adjoining cratons
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 4
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    Glacier surface velocities in the Ötztal Alps (Austria) (2018)
    PANGAEA
    In:  Supplement to: Stocker-Waldhuber, Martin; Fischer, Andrea; Helfricht, Kay; Kuhn, Michael (2019): Long-term records of glacier surface velocities in the Ötztal Alps (Austria). Earth System Science Data, 11(2), 705-715, https://doi.org/10.5194/essd-11-705-2019
    Details
    Publication Date: 2024-07-09
    Description: Glacier surface velocities are measured on four neighbouring glaciers in the Ötztal Alps (Austria). Measurements of the annual horizontal flow velocity (Δs/a [m/a]) on Hintereisferner (HEF) were started in 1885 at stone lines (cross-profiles). Annual values for the stone lines are given as mean values from the stones at the cross-profiles. On Kesselwandferner, the annual horizontal (Δs/a [m/a]) and vertical velocities (Δv/a [m/a], positive upwards and negative downwards) are measured at ablation and accumulation stakes since 1965. On Taschachferner (TSF) and Gepatschferner (GPF), the records of annual and subseasonal horizontal flow velocities at ablation stakes were started in 2009. The data series continues annually, see: doi:10.1594/PANGAEA.928360.
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 5
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    Heterotrophic carbon production of planktonic prokaryotes in the water column during cruise ECO2-6 (2013)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Keywords: Bottle, Niskin 5-L; bottle/B1; bottle/B2; Date/Time of event; DEPTH, water; ECO2; ECO2-6; ECO2-6-19; ECO2-6-6; Elevation of event; Event label; Incorporation of radioactive label (Smith and Azam, 1992); Latitude of event; Longitude of event; NIS_5L; Panarea; Prokaryotes, production; Sub-seabed CO2 Storage: Impact on Marine Ecosystems
    Type: Dataset
    Format: text/tab-separated-values, 6 data points
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  • 6
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    Geochemistry of B3 field (southern Baltic Sea) sediment core StBar-2012-3-15a (2014)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Keywords: Alkalinity, total; Ammonium; B3 field site; Carbon, inorganic, dissolved; Core section label; DEPTH, sediment/rock; ECO2; Hydrogen sulfide; Methane, sediment; NC; Niemistoe corer; Phosphate; St. Barbara; StBar-2012-3; StBar-2012-3-15; StBar-2012-3-15a; Sub-seabed CO2 Storage: Impact on Marine Ecosystems; Sulfate
    Type: Dataset
    Format: text/tab-separated-values, 46 data points
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  • 7
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    Geochemistry of B3 field (southern Baltic Sea) sediment core StBar-2012-3-19a (2014)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Keywords: Alkalinity, total; Ammonium; B3 field site; Carbon, inorganic, dissolved; Core section label; DEPTH, sediment/rock; ECO2; Hydrogen sulfide; Methane, sediment; NC; Niemistoe corer; Phosphate; St. Barbara; StBar-2012-3; StBar-2012-3-19; StBar-2012-3-19a; Sub-seabed CO2 Storage: Impact on Marine Ecosystems; Sulfate
    Type: Dataset
    Format: text/tab-separated-values, 46 data points
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  • 8
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    Geochemistry of B3 field (southern Baltic Sea) sediment core StBar-2012-3-22a (2014)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Keywords: Alkalinity, total; Ammonium; B3 field site; Carbon, inorganic, dissolved; Core section label; DEPTH, sediment/rock; ECO2; Hydrogen sulfide; Methane, sediment; NC; Niemistoe corer; Phosphate; St. Barbara; StBar-2012-3; StBar-2012-3-22; StBar-2012-3-22a; Sub-seabed CO2 Storage: Impact on Marine Ecosystems; Sulfate
    Type: Dataset
    Format: text/tab-separated-values, 46 data points
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  • 9
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    Continuous pCO2 measurements with a multiple fibre optics device at station MUFO-6 during cruise ECO2-8 (2015)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Keywords: Carbon dioxide, partial pressure; DATE/TIME; DEPTH, water; ECO2; ECO2-8; ECO2-8-MUFO-6; MUFO; Multi fibre optics sensor mooring; Panarea; Sub-seabed CO2 Storage: Impact on Marine Ecosystems; Zodiac
    Type: Dataset
    Format: text/tab-separated-values, 1036 data points
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  • 10
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    REVEALS reconstruction of past vegetation cover with original RPP values for Asian samples (2023)
    PANGAEA
    Details
    Publication Date: 2024-07-09
    Description: This data set presents the reconstructed vegetation cover for 533 Asian sites based on harmonized pollen data from the data set LegacyPollen 2.0 (https://doi.pangaea.de/10.1594/PANGAEA.929773). Sugita's REVEALS model (2000) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by accounting for taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal and forest cover was reconstructed. Values for relative pollen productivity and fall speed from the synthesis from Wiezcorek and Herzschuh (2010) were used for the reconstruction of vegetation cover. The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with reconstructed vegetation cover for all continents with original parameters. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.
    Keywords: 11-CH-12A; 11CH17A_Pollen; 16-KP-01-L02-Long3; 880; Abies, cover; Acacia, cover; Acanthaceae, cover; Acer, cover; Aceraceae, cover; ACHIT8; ACHITNUR; Achit-Nur, Mongolia; ACHITNUR8; Achit Nur 8; Achit Nur Lake; ACHITNUUR; Achit Nuur; Acoraceae, cover; Actinidiaceae, cover; Adoxaceae, cover; Adycha_River; Adycha River; Aesculus, cover; AGHNAGHA; Aghnaghak; Aglaia, cover; AHUNG; Ahung Co; AIBI; Aibi Lake; Ailanthus, cover; Aizoaceae, cover; AKKOL; Akkol Lake; AKTEREK; Ak Terek; AKULININ; Akulinin Exposure P1282; AL3; Alangium, cover; Albizia, cover; Alchornea, cover; Allophylus, cover; ALMALOU3; Alnus, cover; Altingia, cover; ALUT; Alut Lake; Amaranthaceae, cover; Amaryllidaceae, cover; AMBA; Amba River; AMGUEMA1; AMGUEMA2; Amguema River 1; Amguema River 2; Ampelopsis, cover; Anacardiaceae, cover; Anguli Nur Lake; ANGUNUR; Annona, cover; Antidesma, cover; Aphanamixis, cover; Apiaceae, cover; Apocynaceae, cover; Apodytes, cover; Aporosa, cover; Aquifoliaceae, cover; Araceae, cover; ARAL86; Araliaceae, cover; Arctic Ocean; Arctostaphylos, cover; Ardisia, cover; Area; Arecaceae, cover; ARKIDA_Pollen; Artemisia, cover; Asia; Asparagaceae, cover; Asphodelaceae, cover; ASTAAL13_Pollen; Asteraceae, cover; Avicennia, cover; AWI_Envi; AWI Arctic Land Expedition; AYONGWA; Ayongwama Co; Baahar Nuur Lake; BAAHNUUR; BAIDARA; Baidara, Russia; Baihe; BAIHE; Baika; BAIKA2; Baikal_Lake-CON01-603-5; Baikal_Lake-CON01-605-3; Baikal_Lake-CON01-605-5; BAIKAL606-3; Baikal CON01-606-3; Baikal Lake-CON01-603-5; Baikal Lake-CON01-605-3; Baikal Lake-CON01-605-5; Baiyangdian Lake GY; BAIYANGGY; BAJIAO; Bajiaotian; Bakaly; BAKALY_neotoma; BALIKUN; Balikun Lake; Balsaminaceae, cover; BANGONG; Bangong Co Lake; BARABA; Barbarina_Tumsa; BARKOLBLK6E; Barkol Lake BLK06E; Basin; Bauhinia, cover; BAYANBY; BAYANCH; Bayanchagan Lake BY; BEIDAWA; Beidawan; BEIHAIGK10; Beihai GK10; BEILIKEK; Beilikekule Lake; Belaya Skala Exposure; BELSKALA; Berberidaceae, cover; BEREGOV2_Pollen; Berelyekh River; BETENK; Betenkyos Adycha river; Betula, cover; Betulaceae, cover; Biebersteiniaceae, cover; Big_Yarovoe_Lake_2008-3; Bignoniaceae, cover; Big Yarovoe Lake; BOGUDA; BOLOTNYI; Bolotnyii Stream Exposure 117; BOLS1TZ1_Pollen; Bolshaya Kuobakh-Baga River; Bolshaya Kuropatochya River; Bolshaya Kuropatochya River P7; Bolshoe Eravnoe Lake, Russia; Bolshoe Toko; BOLVAN25_Pollen; BOLVAN48_Pollen; Bombax, cover; Boraginaceae, cover; Bosten; Boyiqiao ZK01; BOYIQZK1; Brassicaceae, cover; Broussonetia, cover; Buddleja, cover; BUGRIST; Bugristoe, Russia; Buxus, cover; Byllatskoye; Calculated average/mean values; Calendar age, maximum/old; Calendar age, mean; Calendar age, median; Calendar age, minimum/young; Callicarpa, cover; Camellia, cover; Campanulaceae, cover; CAMPING; CANGUMI; Cangumiao; Cannabaceae, cover; CAOTAN2002; Caotanhu 2002; Cape Shpindler, Yugorski Peninsula, Russia; Capparaceae, cover; Capparis, cover; Caprifoliaceae, cover; Caragana, cover; Carya, cover; Caryophyllaceae, cover; Casearia, cover; Caspian Sea; Castanea, cover; Castanopsis, cover; Casuarina, cover; Catalpa, cover; Cedrus, cover; Celastraceae, cover; Celtis, cover; Cephalanthus, cover; Cercidiphyllum, cover; Cercis, cover; CHABADA1; CHABADA2; ChabadaII; Chabada Lake, Russia; CHADIAN; Chadianpo; Chaginskoe; CHAIWOCKF; Chaiwopu Lake CKF; Chamaecyparis, cover; Changjiang CM97; Changjiang HQ98; CHANGJICM97; CHANGJIHQ98; CHANGNING_Pollen; Changshan; CHANGSHAN; CHANGXING; Changxing Island; CHAOCH1; Chaohu Lake CH1; CHARIMUCH; Charisu/Muchang profile; Chatanga2011; CHENGCH2; Chenghai CH2; Cheremushka_Bog; Cheremushka Bog; Chernaya_Gorka; CHERNOE; Chernoe Lake, Russia; CHERNYAR; Chernyii Yar Exposure 955; Cherny Yar, Russia; CHERYAR; CHESNOK; Chesnok Peat Irtysh River; Chifeng-Qiguo Mt.; CHIFEQIGU; China; Chistoye Lake; CHITSAI; Chitsai Lake; CHUANGY; Chuangye; Chukotka 2018; Cistaceae, cover; Citrus, cover; Claoxylon, cover; Clausena, cover; Clerodendrum, cover; Clethra, cover; Clethraceae, cover; Clusiaceae, cover; Co1412; Cocculus, cover; Colchicaceae, cover; Combretaceae, cover; Commelinaceae, cover; COMPCORE; Composite Core; Continent; Convolvulaceae, cover; Co Qongjiamong; Core1; Core13; Core2; Core20; Core86; Cornaceae, cover; Cornus, cover; Corylus, cover; Cotinus, cover; Crassulaceae, cover; Crataegus, cover; Cratoxylum, cover; Cryptomeria, cover; CS98-10; Cucurbitaceae, cover; Cunninghamia, cover; Cupressaceae, cover; Cupressus, cover; Cyclobalanopsis, cover; Cyclocarya, cover; Cyperaceae, cover; DABA8; DABANUR; Daba-Nur, Mongolia; Daba Nur Lake; DABSANCK181; Dabsan Lake CK1/81; Dacrydium, cover; Dadiwan_2007; Dadiwan_2008; DADIWAN07; DADIWAN08; DAHAIZI; Dahaizi Lake; DAHU_Pollen; DAIHAI99A; DAIHAI99B; Daihai Lake 99a; Daihai Lake DH99B; Dajiuhu_2013; DAJIUHU2013; DAJIUHUC1; Dajiuhu Lake C1; DALAINUR; Dalai Nur Lake-Haiyan; Dalbergia, cover; DALINURHAO; Dali Nur-Haoluku Lake; DALINURJIAN; Dali Nur-Jiangjunpaozi Lake; DALINURLIU; Dali Nur-Liuzhouwan Lake; Damagou; DAMAGOU; Dashan; DASHAN; DASHUI; Dashuitang; Data ID; Datiscaceae, cover; Daxigou; DAXIGOU; DAZIYIN; Daziying; Decaspermum, cover; DENGJIAC; Dengjiacun; DEPTH, sediment/rock; DERPUT; Derput, Russia; Deutzia, cover; Diameter; DIAOJIAO; Diaojiaohaizi DJ; Diapensiaceae, cover; DIMA1; DIMA2; DIMA3; DIMA4; Dingnan; DINGNAN; Dingxi; DINGXI; Dioscoreaceae, cover; Diospyros, cover; Diplospora, cover; Dipsacaceae, cover; Dipterocarpaceae, cover; Distylium, cover; Dlinnoye_Lake; Dlinnoye Lake; Dodonaea, cover; Dolgoe_Ozero; Dolgoe Ozero; DONGDAO; Dongdaohaizi B; DONGGAN; Dongganchi; DONGGI1790; Dongguan_PK16; DONGGUPK16; DOOD4; DOODNUR; Dood-Nur, Mongolia; Dood Nur Lake; DOUCO; Douco Lake; DRILL; Drilling/drill rig; Droseraceae, cover; East Siberian Sea Coast 11; Ebenaceae, cover; EBINUR; Ebinur Lake; Ebinur Lake SW; EBINURSW; EK4; Elaeagnaceae, cover; Elaeagnus, cover; Elaeocarpaceae, cover; Elaeocarpus, cover; Eleutherococcus, cover; ELGENNYA; Elgennya Lake; Elgygytgyn_Lake_P2; Elgygytgyn crater lake, Sibiria, Russia; Elgygytgyn lake; Elgygytgyn Lake P2; Elikchan 4 Lake; EN18218; Endospermum, cover; Engelhardia, cover; ENM109; ENMYN; Enmynveem Malyi Anyui; Enmynveem River; Entada, cover; ENTARNOY; Entarnoye; Ephedra, cover; Ephedraceae, cover; ERAVNOE; ERHAIES; Erhai Lake ES; Ericales, cover; Eriobotrya, cover; ERLONGWA; Erlongwan Maar Lake; Eucalyptus, cover; Euonymus, cover; Euphorbiaceae, cover; Euptelea, cover; Eupteleaceae, cover; Eurya, cover; Event label; Excoecaria, cover; Fabaceae, cover; Faddeyevskiy; FADEYEVS; Fagaceae, cover; Fagraea, cover; Fagus, cover; FENGNIN; Fengning; FENZHU; Fenzhuang; Ficus, cover; Flacourtia, cover; Flacourtiaceae, cover; Flueggea, cover; Forest, cover; fossil pollen; Foyechi; FOYECHI; Frangula, cover; Frankeniaceae, cover; Fraxinus, cover; GANHAI; Ganhai Lake; GANLAN; Ganlanba; Gantang; GANTANG; GAOXI; Gaoximage; Garcinia, cover; Gardenia, cover; GC; GCUWI; GEK; Gek Lake; GENGGA_Pollen; Genista, cover; Gentianaceae, cover; Geological profile sampling; GEOPRO; Geraniaceae, cover; Gesneriaceae, cover; GHARASO_Pollen; Ginkgo, cover; GLADKOYE; Gladkoye Bog; Global River Discharge; Glochidion, cover; Glukhoye Lake; GLUPEAT; Glyptostrobus, cover; GOLUBOY; Goluboye Lake; Gomishan, Islamic Republic of Iran; GONGHAI; Gonghai Lake; Gounong Co KX-1; GOUNONGKX1; Gravity corer; Gravity corer, UWITEC; Grewia, cover; Grossulariaceae, cover; GRUSHA; Grusha Lake; GS05; GS18; GUANGFU; Guangfulin; GUANGRU1; Guangrunpo 1; GUANGTA; Guangtangtou; GUCHENG; Gucheng Lake; Gulf of Tartary; GUNNUR; Gun-Nur, Mongolia; GUNNURLA; Gun Nur Lake; Gur_sample; GURSKII; Gurskii Peat; Gymnosporia, cover; GYTGYKAI; Gytgykai Lake; HACHIHAM; Hachihama; Hachiman-Numa; HACHI-NU; Hailaer; HAILAER; Haiyuan; HAIYUAN; Halali; HALALI; HALIGU; Haligu Lake; Hamaertai Lake Ha2; HAMAHA2; Hamamelidaceae, cover; Hamamelis, cover; HANHAIH1; Hanhai Lake H1; HARBA; Harbaling; HCGA05_Pollen; HCGL02_Pollen; Headwaters Opasnaya River (mine shaft); Helicia, cover; Heliotropium, cover; Helwingia,
    Type: Dataset
    Format: text/tab-separated-values, 47321056 data points
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