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German Centre for Integrative Biodiversity Research (iDiv) – Halle-Jena-Leipzig, Puschstrasse 4, 04103, Leipzig, GermanyFrancesco Maria SabatiniMartin-Luther-Universität Halle-Wittenberg, Institut für Biologie, Am Kirchtor 1, 06108, Halle, GermanyFrancesco Maria SabatiniHumboldt-Universität zu Berlin, Geography Department, Unter den Linden 6, 10099, Berlin, GermanyHendrik BluhmFrankfurt Zoological Society, Bernhard-Grzimek-Allee 1, 60316, Frankfurt, GermanyZoltan KunNGO “Transparent World”, Rossolimo str. 5/22, building 1, 119021, Moscow, RussiaDmitry AksenovEUROPARC-Spain/Fundación Fernando González Bernáldez. ICEI Edificio A. Campus de Somosaguas, E28224, Pozuelo de Alarcón, SpainJosé A. AtauriThe Danish Nature Agency, Gjøddinggård, Førstballevej 2, DK-7183, Randbøl, DenmarkErik BuchwaldSapienza University of Rome, Department of Environmental Biology, P.le Aldo Moro 5, 00185, Rome, ItalySabina BurrascanoRéserves Naturelles de France, La Bourdonnerie, Dijon cedex, 21000, FranceEugénie CateauPSEDA-ILIRIA. Forestry department, Tirana, 1000, AlbaniaAbdulla DikuCentre for Applied Ecology “Professor Baeta Neves” (CEABN), InBIO, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349‐017, Lisbon, PortugalInês Marques DuarteParque Nacional de Garajonay. Avda. V Centenario, edif. Las Creces, local 1, portal 3, 38800 San Sebastian de La Gomera, Tenerife, SpainÁngel B. Fernández LópezUniversity of Torino, Department DISAFA L.go Paolo Braccini 2, Grugliasco, 10095, ItalyMatteo GarbarinoForest Research Institute, Vassilika, 57006, Thessaloniki, GreeceNikolaos GrigoriadisCentre for Ecological Research, Institute of Ecology and Botany, Alkotmány u. 2-4, 2163, Vácrátót, HungaryFerenc HorváthFaculty of Forestry, University of Agriculture in Krakow, aleja 29-Listopada 46, 31-415, Krakow, PolandSrđan KerenLatvian State Forest Research Institute “Silava”, Rigas street 111, Salaspils, LV-2169, LatviaMara KitenbergaInstitute for Nature Conservation of Vojvodina Province, Radnička 20a, Novi Sad, 21000, SerbiaAlen KišUniversity of Tartu, Institute of Ecology and Earth Sciences, Vanemuise 46, EE-51014, Tartu, EstoniaAnn KrautCentre for Econics and Ecosystem Management, Faculty of Forest and Environment, Eberswalde University for Sustainable Development, Alfred-Möller-Str. 1, 16225, Eberswalde, GermanyPierre L. IbischUniversité de Toulouse, INRAE, UMR DYNAFOR, 24 Chemin de Borde-Rouge Auzeville CS 52627, Castanet-Tolosan, 31326, FranceLaurent LarrieuCRPF-Occitanie, antenne de Tarbes, place du foirail, 65000, Tarbes, FranceLaurent LarrieuMediterranean University of Reggio Calabria, Agraria Department, Loc. Feo di Vito, 89122, Reggio Calabria, ItalyFabio LombardiUniversity of Novi Sad, Institute of Lowland Forestry and Environment, Antona Cehova 13d, Novi Sad, 21102, SerbiaBratislav MatovicWorld Wide Fund for nature (CEE), Lunga street 190, Brasov, 500051, RomaniaRadu Nicolae MeluNorthwest German Forest Research Institute, Department Forest Nature Conservation, Professor-Oelkers-Straße 6, 34346, Hann. Münden, GermanyPeter MeyerAsplan Viak A.S.Kjörboveien 20, postboks 24, N-1300, Sandvika, NorwayRein MidtengUniversity of Zagreb, Faculty of Forestry, Svetosimunska cesta 25, 10000, Zagreb, CroatiaStjepan MikacCzech University of Life Sciences, Faculty of Forestry and Wood Sciences, Kamýcka cesta 1176, CZ-, 16521, Praha6-Suchdol, Czech RepublicMartin MikolášPRALES, Odtrnovie 563, SK-01322, Rosina, SlovakiaMartin MikolášVytautas Magnus University, K. Donelaičio g. 58, LT-44248, Kaunas, LithuaniaGintautas MozgerisUniversity of Forestry, Dendrology Department, bulevard “Sveti Kliment Ohridski” 10, 1756, Sofia, BulgariaMomchil PanayotovSlovenia Forest Service, Department for forest management planning, Vecna pot 2, 1000, Ljubljana, SloveniaRok PisekCentre for Applied Ecology “Professor Baeta Neves” (CEABN), InBIO, School of Agriculture, University of Lisbon, Tapada da Ajuda 1349‐017, Lisbon, PortugalLeónia NunesGreensway AB, Ulls väg 24A, 756 51, Uppsala, SwedenAlejandro RueteFreelance forest expert and book author, Vienna, AustriaMatthias SchickhoferSs. Cyril and Methodius University in Skopje, Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering, Department of Botany and Dendrology, P.O. Box 235, MK-1000, Skopje, North MacedoniaBojan SimovskiSwiss Federal Research Institute for Forest, Snow and Landscape Research WSL, Forest Resources and Management, Zürcherstrasse 111, 8903, Birmensdorf, SwitzerlandJonas StillhardUniversity of Novi Sad, Institute of Lowland Forestry and Environment, Antona Cehova 13d, Novi Sad, 21000, SerbiaDejan StojanovicDepartment of Forest Biodiversity, University of Agriculture, Kraków, PolandJerzy SzwagrzykUniversity of Eastern Finland, School of forest Sciences, Yliopistokatu 7, 80100, Joensuu, FinlandOlli-Pekka TikkanenAgricultural University of Tirana, Forestry Department, Kodër Kamëz, SH1, 1029, Tirana, AlbaniaElvin ToromaniWorld Wide Fund for nature (DCP) Ukraine, Mushaka 48, Lviv, 79011, UkraineRoman VolosyanchukEcosphera NGO, Kapushans’ka 82a, Uzhhorod, 88000, UkraineRoman VolosyanchukSilva Tarouca Research Institute, Department of Forest Ecology, Lidická 25/27, 602 00, Brno, Czech RepublicTomáš VrškaCentre for Econics and Ecosystem Management, Faculty of Forest and Environment, Eberswalde University for Sustainable Development, Alfred-Möller-Str. 1, 16225, Eberswalde, GermanyMarcus WaldherrInstitute of Experimental Botany of the National Academy of Sciences of Belarus, Laboratory of Productivity & Stability of Plant Communities, 220072, Academicheskaya St. 27, Minsk, BelarusMaxim YermokhinInstitute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, 2 Gagarin Street, 1113, Sofia, BulgariaTzvetan ZlatanovSaint-Petersburg State University, Department of Vegetation Science, University Embankment, 7/9, St Petersburg, 199034, RussiaAsiya ZagidullinaHumboldt-Universität zu Berlin, Geography Department & Integrative Research Institute on Transformation in Human-Environment Systems, Unter den Linden 6, 10099, Berlin, GermanyTobias KuemmerleCorrespondence to
Francesco Maria Sabatini. More

Melted quartz grainsCrystalline quartz melts between 1670 °C (tridymite) and 1713 °C (cristobalite), and because quartz is pervasive and easily identified, melted grains serve as an important temperature indicator. At TeH, we observed that unmelted potsherds displayed no melted quartz grains, indicating exposure to low temperatures. On the other hand, most quartz grains on the surfaces of pottery, mudbricks, and roofing clay exhibited some degree of melting, and unmelted quartz grains were rare. Nearly all quartz grains found on broken, unmelted surfaces of potsherds were also unmelted. On melted pottery and mudbricks, melted quartz has an estimated density of 1 grain per 5 mm2.Melted quartz grains at TeH exhibit a wide range of morphologies. Some show evidence of partial melting that only melted grain edges and not the rest of the grain (Figs. 22, 23). Others displayed nearly complete melting with diffusion into the melted Ca–Al–Si matrix of pottery or mudbrick (Fig. 22). Melted quartz grains commonly exhibit vesiculation caused by outgassing (Figs. 22, 23), suggesting that those grains rose above quartz’s melting point of ~ 1713 °C.Figure 22SEM images of melted quartz grains on melted potsherd from the palace. (a) Highly melted quartz grain from the upper surface of melted pottery; shows flow lines of molten quartz in darker ‘neck’ at upper right; (b) manually constructed EDS-based phase map showing 100% quartz grain (green) embedded in Ca–Al–Si matrix of melted pottery (red); blue marks mixing zone between SiO2 and matrix at approximately  > 1713 °C, the melting point of quartz. Yellow arrow points to area depleted in oxygen, indicating high-temperature transformation to elemental Si mixed with melted SiO2. (c) Highly melted quartz grain; (d) manually constructed EDS-based phase map showing diffusion/mixing zone in blue with arrow pointing to bubble, indicating outgassing as grain reached temperatures above its melting point. (e) Quartz grain that has almost completely melted; (f) manually constructed EDS-based phase map showing the small remnant of a melted quartz grain (green) with a wide mixing zone (blue).Full size imageFigure 23SEM images of melted quartz grains on melted mudbrick from the palace. (a) Highly melted quartz grain; (b) manually constructed EDS-based phase map indicates center is pure SiO2 surrounded by melted mudbrick. Arrow points to vesicles indicating outgassing as grain temperature rose above ~ 1713 °C, the melting point of quartz. (c) The surface of a flattened quartz grain showing flow marks toward the upper right. High temperatures are required to lower the viscosity sufficiently for quartz to flow. (d) Manually constructed EDS-based phase map with an arrow pointing to vesicles indicating outgassing at high temperatures. (e) Close up of grain in panel ‘c’ showing flow marks (schlieren) at arrows. (f) Shattered, melted quartz splattered onto mudbrick meltglass; (g) manually constructed EDS-based phase map indicating that the blue area is SiO2; the yellow area is a shattered, thermally altered Fe-oxide grain.Full size imageAn SEM–EDS elemental map of one melted grain showed that the quartz had begun to dissociate into elemental Si (Fig. 22b). Another grain (Fig. 23c–e) displayed flow marks consistent with exposure to temperatures above 1713 °C where the viscosity of quartz falls low enough for it to flow easily. Another SEM–EDS analysis confirmed that one agglutinated mass of material is 100 wt.% SiO2 (Fig. 23f, g), suggesting that this polycrystalline quartz grain shattered, melted, and partially fused again.Discussion of melted quartzMoore et al.17 reported that during heating experiments, many quartz grains  50-µm-wide remained visually unaltered up to ~ 1700 °C. By 1850 °C, all quartz grains fully melted. These experiments establish a particle-size dependency and confirm confirmed the melting point for  > 50-µm-wide TeH quartz grains between ~ 1700–1850 °C. Melted  > 50-µm-wide quartz grains on the surfaces of melted pottery and mudbrick from the TeH destruction layer indicate exposure to these unusually high temperatures  > 1700 °C.Previously, Thy et al.70 proposed that glass at Abu Hureyra did not form during a cosmic impact, but rather, formed in biomass slag that resulted from thatched hut fires. However, Thy et al. did not determine whether or not high-temperature grains existed in the biomass slag. To test that claim, Moore et al.17 analyzed biomass slag from Africa and found only low-temperature melted grains with melting points of ~ 1200 °C, consistent with a temperature range for biomass slag of 1155–1290 °C, as reported by Thy et al.71. Upon testing the purported impact glass from Abu Hureyra, Moore et al.17 discovered high-temperature mineral grains that melt in the range of 1713° to  > 2000 °C, as are also found in TeH glass. These test results suggest that the melted glass from Abu Hureyra must have been exposed to higher temperatures than those associated with fires in thatched huts. Because of the presence of high-temperature minerals at TeH, we conclude that, as at Abu Hureyra, the meltglass could not have formed simply by burning thatched huts or wood-roofed, mudbrick buildings.Melted Fe- and Si-rich spherulesThe presence of melted spherulitic objects (“spherules”) has commonly been used to help identify and investigate high-temperature airburst/impact events in the sedimentary record. Although these objects are referred to here as “spherules,” they display a wide range of other impact-related morphologies that include rounded, sub-rounded, ovate, oblate, elongated, teardrop, dumbbell, and/or broken forms17,72,73,74,75,76,77,78,79,80,81,82. Optical microscopy and SEM–EDS are commonly used to identify and analyze spherules and the processes by which they are formed. Care is needed to conclusively distinguish high-temperature spherules produced by cosmic impacts from other superficially similar forms. Other such objects that frequently occur in sediments include anthropogenic spherules (typically from modern coal-fired power plants), authigenic framboids (Supporting Information, Fig. S7), rounded detrital magnetite, and volcanic spherules.Spherules in TeH sediment were investigated from stratigraphic sequences that include the MB II destruction layer at four locations: palace, temple, ring road, and wadi (Fig. 24). For the palace (Field UA, Square 7GG), the sequence spanned 28 cm with 5 contiguous samples of sediment ranging from 3-cm thick for the MB II destruction layer to 13-cm thick for some outlying samples. In the palace, 310 spherules/kg (Fig. 24d) were observed in the destruction layer with none found in samples above and below this layer. For the temple (Field LS, Square 42J), 5 continuous samples spanned 43 cm and ranged in thickness from 6 to 16 cm; the MB II layer contained ~ 2345 Fe- and Si-rich spherules/kg with 782/kg in the sample immediately below and none at other levels (Fig. 24c). Six contiguous samples from the ring road (Field LA, Square 28 M) spanned 30 cm with all 5 cm thick; the MB II destruction layer at this location contains 2150 spherules/kg with none detected in younger or older samples (Fig. 24b). Five discontinuous samples from the wadi spanned 170 cm, ranging from 10-cm thick for the destruction layer up to 20-cm thick for other samples; the MB II destruction layer at this location contained 2780 spherules/kg with none in samples from other levels (Fig. 24a, Supporting Information, Table S3). Notably, when melted mudbrick from the ring road was being mounted for SEM analysis, numerous loose spherules were observed within vesicles of the sample, confirming a close association between the spherules and meltglass. At all four locations, the peaks in high-temperature spherule abundances occur in the MB II destruction layer dating to ~ 1650 BCE.Figure 24Spherule abundances. (a)–(d). Number per kg for Fe- and S-rich spherules from 4 locations. Depths are in cm above or below the bottom of the destruction layer.Full size imageSEM images of spherules are shown in Figs. 25, 26, 27 and 28, and compositions are listed in Supporting Information, Table S4. The average spherule diameter was 40.5 µm with a range of 7 to 72 µm. The dominant minerals were Fe oxides averaging 40.2 wt.%, with a range of up to 84.1 wt.%; elemental Fe with a range of up to 80.3 wt.%; SiO2 averaging 20.9 wt.%, ranging from 1.0 to 45.2 wt.%; Al2O3 averaging 7.8 wt.% with a range of up to 15.6 wt.%; and TiO2 averaging 7.1 wt.% with a range of up to 53.1 wt.%. Fourteen spherules had compositions  > 48 wt.% of oxidized Fe, elemental Fe, and TiO2; five spherules contained  75 wt.% Fe with no Ti. Eight of 23 spherules analyzed contained detectable levels of Ti at up to 53.1 wt.%.Figure 25SEM images of mostly silica-rich spherules from TeH. (a)–(d) Representative spherules from the ring road on the lower tall. SEM images of iron-rich spherules. (e)–(f) Fe-rich spherules from the temple complex. (g) temple spherule containing ~ 3.7 wt.% Cr. (h) Broken, vesicular spherule from temple containing 1.4 wt.% Ni and 3.7 wt.% Cr. SEM images of titanium-rich spherules. Ti content of these ranges from 18.9 to 1.2 wt.%, averaging 10.7 wt.%. (i)–(k) Spherules from the ring road. (l) Spherule from the wadi site.Full size imageFigure 26SEM image of rare-earth (REE) spherule. (a) REE-rich 72-µm-wide spherule from the palace, dominantly composed of Fe, La, Ce, and O. (b) Close up of REE blebs found on the spherule. (c)–(f) SEM–EDS elemental maps showing composition. La = 15.6 wt.% and Ce = 21.0 wt.%. Ce is enriched over Fe and La in the middle part of the spherule, as seen in panels ‘d’ through ‘f’.Full size imageFigure 27SEM images of a spherule mainly composed of Fe and Si. (a) Fe–Ti-rich 54-µm-wide spherule from the palace. Spherule displays a protrusion to the left, suggesting aerodynamic shaping when molten, after which the tail detached. (b) A focused ion beam (FIB) was used to section the spherule, revealing inclusions of wassonite or titanium sulfide (TiS; yellow arrows) that are lighter-colored than the matrix. (c)–(f) Color-coded SEM–EDS elemental maps, showing the distribution of Ti, S, Si, and Fe and the location of the TiS grains. The spherule is dominantly composed of Fe and Si with minor amounts of Ti and S found in TiS inclusions.Full size imageFigure 28Fe-rich spherules embedded in meltglass. (a) Optical photomicrograph of a 167-µm-wide piece of meltglass with embedded Fe-rich spherules. (b) SEM image of same grain as in panel ‘a’. Melted quartz grain (Qtz) is embedded in Ca–Al–Si-rich matrix, which has the same composition as melted mudbrick. (c) SEM close-up image of the boxed area and panel ‘b’, showing splattered Fe-rich spherule.Full size imageTwo unusual spherules from the palace contain anomalously high percentages of rare-earth elements (REEs) at  > 37 wt.% of combined lanthanum (La), and cerium (Ce) (Fig. 26), as determined by preliminary measurements using SEM–EDS. Minor oxides account for the rest of the spherules’ bulk composition (Table S1).One 54-µm-wide sectioned spherule contains titanium sulfide (TiS) with a melting point of ~ 1780° C. TiS, known as wassonite, was first identified in meteorites (Fig. 27) and has been reported in impact-related material17,81,83. However, TiS sometimes occurs as an exsolution product forming fine networks in magnetite and ilmenite and can be of terrestrial origin.One unusual piece of 167-µm-wide Ca–Al–Si meltglass contains nearly two dozen iron oxide spherules on its surface (Fig. 28). The meltglass contains a completely melted quartz grain as part of the matrix (Fig. 28b). Most of the spherules appear to have been flattened or crushed by collision with the meltglass while they were still partially molten (Fig. 28c).Discussion of spherules and meltglassMelted materials from non-impact-related combustion have been reported in multiple studies. Consequently, we investigated whether Ca-, Fe-, and Si-rich spherules and meltglass (mudbrick, pottery, plaster, and roofing clay) may have formed normally, rather than from a cosmic impact event. For example, (i) glassy spherules and meltglass are known to form when carbon-rich biomass smolders below ground at ~ 1000° to 1300 °C, such as in midden mounds71. They also form in buried peat deposits84, underground coal seams85, burned haystacks86, and in large bonfires, such as at the Native American site at Cahokia, Illinois, in the USA87. (ii) Also, ancient fortifications (hillforts) in Scotland and Sweden, dating from ~ 1000 BCE to 1400 AD, have artificially vitrified walls that melted at temperatures of ~ 850° to 1000 °C88. (iii) Partially vitrified pottery and meltglass derived from the melting of wattle and daub (thatch and clay) with estimated temperatures of ~ 1000 °C have been reported in burned houses of the Trypillia culture in Ukraine89,90. (iv) Vitrified mudbricks and pottery that melted at 17 investigated biomass glass from midden mounds in Africa and found no high-temperature minerals. For this contribution, we used SEM–EDS to examine aluminosilicate meltglass from an underground peat fire in South Carolina, USA; meltglass in coal-fired fly ash from New Jersey, USA; and mining slag from a copper mine in Arizona, USA. All these meltglass examples display unmelted quartz and contain no other high-temperature melted grains, consistent with low-temperature melting at  97% wt.% FeO, as are found at TeH. Nor can these low temperatures produce meltglass and spherules embedded with melted zircon (melting point = 1687 °C), chromite (2190 °C), quartz (1713 °C), platinum (1768 °C), and iridium (2466 °C). Moore et al.17 confirmed that the melting of these high-temperature minerals requires minimum temperatures of ~ 1500° to 2500 °C.This evidence demonstrates that although the matrix of the spherules and meltglass at TeH likely experienced incipient melting at temperatures lower than ~ 1300 °C, this value represents only the minimum temperature of exposure, because the high-temperature minerals embedded in them do not melt at such low temperatures. Instead, the spherules and meltglass at TeH must have reached temperatures greater than ~ 1300 °C, most likely involving brief exposure to ambient temperatures of ~ 2500 °C, the melting point of iridium. These temperatures far exceed those characteristic of city fires and other types of biomass burning. In summary, all of this evidence is consistent with very high temperatures known during cosmic impacts but inconsistent with other known natural causes.Calcium carbonate spherules and plasterIn sediments of the destruction layer, we observed amber-to-off-white-colored spherules (Fig. 29) at high concentrations of ~ 240,000/kg in the palace, ~ 420/kg in the temple, ~ 60/kg on the ring road, and ~ 910/kg in the wadi (Supporting information, Table S2). In all four profiles, the spherules peak in the destruction layer with few to none above or below. Peak abundances of calcium carbonate spherules are closely associated with peak abundances of plaster fragments, which are the same color. By far the most spherules (~ 250× more) occurred in the destruction layer of the palace, where excavations showed that nearly every room and ceiling was surfaced with off-white lime-based plaster. Excavators uncovered high-quality lime plaster fragments still adhering to mudbricks inside the MB II palace complex, and in one palace room, we uncovered fragments of melted plaster (Fig. 29e). In contrast, lime plaster was very rarely used in buildings on the lower tall, including those near the temple.Figure 29Images of calcium carbonate spherules and melted plaster from TeH. (a) Photomicrographs of translucent, amber-colored CaCO3 spherules from the destruction layer in the palace. (b) SEM image of 83-µm carbonate spherule with impact or outgassing crater at arrow. (c) Photomicrograph of ~ 2-mm-wide piece of partially melted palace plaster from oxygen/propylene torch test, showing incipient melting at 1500 °C. Arrows point to hemispheric droplets emerging as spherules. (d) 142-µm cluster of 8 carbonate spherules with apparent impact or outgassing crater at arrow. (e) 64 × 30 mm piece of melted plaster that broke off the palace wall and became melted. It is composed only of calcium, carbon, and oxygen.Full size imageTo explore a potential connection between plaster and spherules, we performed SEM–EDS on samples of the palace plaster. Comparison of SEM–EDS analyses shows that the plaster composition has a  > 96% similarity to the spherule composition: CaCO3 = 71.4 wt.% in plaster versus 68.7 wt.% in the spherules; elemental C = 23.6 versus 26.3 wt.%; SiO2 = 2.4 versus 1.8 wt.%; MgO = 1.7 versus 2.0 wt.%; and SO3 = 0.94 versus 1.2 wt.%. The high carbon percentage and low sulfur content indicate that the plaster was made from calcium carbonate and not gypsum (CaSO4·2H2O). SEM imaging revealed that the plaster contains small plant parts, commonly used in plaster as a binder, and is likely the source of the high abundance of elemental C in the plaster. Inspection showed no evidence of microfossils, such as coccoliths, brachiopods, and foraminifera. The morphology of the spherules indicates that they are not authigenic or biological in origin.Discussion of carbonate plaster and spherulesOne of the earliest known uses of CaCO3-based plaster was in ~ 6750 BCE at Ayn Ghazal, ~ 35 km from TeH in modern-day Amman, Jordan97. At that site, multi-purpose lime plaster was used to make statues and figurines and to coat the interior walls of buildings. Because the production of lime-based plaster occurred at least 3000 years before TeH was destroyed, the inhabitants of TeH undoubtedly were familiar with the process. Typically, lime powder was produced in ancient times by stacking wood/combustibles interspersed with limestone rocks and then setting the stack on fire. Temperatures of ~ 800–1100 °C were required to transform the rocks into crumbly chalk, which was then mixed with water to make hydrated lime and plastered onto mudbrick walls97.At TeH, fragments of CaCO3-based plaster are intermixed in covarying abundances with CaCO3-based spherules with both compositions matching to within 96%. This similarity suggests that the carbonate spherules are derived from the plaster. We infer that the high-temperature blast wave from the impact event stripped some plaster from the interior walls of the palace and melted some into spherules. However, it is difficult to directly melt CaCO3, which gives off CO2 at high temperatures and decomposes into lime powder. We investigated this cycle in a heating experiment with an oxygen/propylene torch and found that we could decompose the plaster at ~ 1500 °C, the upper limit of the heating test, and begin incipient melting of the plaster. The heated plaster produced emergent droplets at that temperature but did not transform into free spherules (Supporting Information, Text S2).Similar spherules have been reported from Meteor Crater, where spherules up to ~ 200 μm in diameter are composed entirely of CaCO3 formed from a cosmic impact into limestone98,99. One of several possible hypotheses for TeH is that during the impact event, the limestone plaster converted to CaO with an equilibrium melting point of 2572 °C. However, it is highly likely that airborne contaminants, such as sodium and water vapor, reacted with the CaO and significantly lowered the melting point, allowing spherule formation at ≥ 1500 °C.The proposed chemical sequence of events of plaster formation and the later impact are as follows:

1.

Limestone was heated to ~ 800–1100 °C, decomposing to quicklime:

$${text{CaCO}}_{{3}} to {text{ CaO }} + {text{ CO}}_{{2}}$$

2.

Quicklime was mixed with water to make a wet plaster:$${text{CaO }} + {text{ H}}_{{2}} {text{O }} to {text{ Ca}}left( {{text{OH}}} right)_{{2}}$$

3.

The plaster hardened and slowly absorbed CO2 to revert to CaCO3:$${text{Ca}}left( {{text{OH}}} right)_{{2}} + {text{ CO}}_{{2}} to {text{ H}}_{{2}} {text{O }} + {text{ CaCO}}_{{3}}$$

4.

The high-temperature impact event melted some plaster into spherules:$${text{CaCO}}_{{3}} to {text{ CaO }}left( {{text{spherules}}} right) , + {text{ CO}}_{{2}} left( { > {15}00^circ {text{C}}} right)$$

5.

CaO spherules slowly absorbed CO2 to revert to CaCO3:$${text{Ca }} + {text{ CO}}_{{2}} to {text{ CaCO}}_{{3}} left( {text{as spherules}} right)$$

General discussion of all spherulesAccording to the previous investigations17,72,81,82, Fe-rich spherules such as those found at TeH typically melt at  > 1538 °C, the melting point of iron (Table 1). Because of the presence of magnetite (Fe3O4) in the REE spherule, its melting point is inferred to be  > 1590 °C (Table 1). The Si-rich spherules are similar in composition to TeH sediment and mudbrick, and thus, we propose that they were derived from the melting of these materials at  > 1250 °C. The carbonate-rich spherules likely formed at  > 1500 °C.Several studies describe a mechanism by which spherules could form during a low-altitude cosmic airburst100,101. When a bolide enters Earth’s atmosphere, it is subjected to immense aerodynamic drag and ablation, causing most of the object to fragment into a high-temperature fireball, after which its remaining mass is converted into a high-temperature vapor jet that continues at hypervelocity down to the Earth’s surface. Depending on the altitude of the bolide’s disruption, this jet is capable of excavating unconsolidated surficial sediments, melting them, and ejecting the molten material into the air as Si- and Fe-rich spherules and meltglass. This melted material typically contains a very low percentage (17.Melted zircons in pottery and mudbricks were observed (Fig. 30) at an estimated density of 1 grain per 20 mm2. On highly melted surfaces, nearly all zircons showed some degree of melting. In contrast, nearly all zircons found on broken interior surfaces were unmelted (Fig. 30d), except those within ~ 1 mm of melted surfaces. This implies that the temperature of the surrounding atmosphere was higher than the internal temperatures of the melting objects. Unmelted potsherds displayed only unmelted minerals.Figure 30SEM images of melted zircon grains. (a) Melted TeH zircon grain with bubbles at yellow arrow due to high-temperature dissociation and/or entrapped porosity. (b) Melted TeH zircon grain decorated with bubbles along the fracture line at upper arrow; arrows labeled “Bd” point to bright granular baddeleyite, ZrO2, formed during the high-temperature dissociation of zircon. (c) Almost fully melted TeH zircon grain mixing into the Ca–Al–Si matrix. (d) A typical unmelted zircon grain from TeH with straight, euhedral edges. Grain shows cracks on the top surface from possible thermal or mechanical damage. (e) For comparison, from cosmic airburst/impact at Dakhleh Oasis in Egypt: melted zircon decorated with lines of bubbles (arrow).Full size imageThe melted zircons in TeH materials exhibit a wide range of morphologies. Most showed evidence of sufficient melting to alter or destroy the original distinctive, euhedral shape of the grains. Also, the grains were often decorated with vesicles that were associated with fractures (Fig. 30a, c).Stoichiometric zircon contains 67.2 wt.% and 32.8 wt.% ZrO2 and SiO2 respectively, but in several TeH samples, we observed a reduction in the SiO2 concentration due to a loss of volatile SiO from the dissociation of SiO2. This alteration has been found to occur at 1676 °C, slightly below zircon’s melting point of 1687 °C103. This zircon dissociation leads to varying ZrO2:SiO2 ratios and to the formation of distinctive granular textures of pure ZrO2, also known as baddeleyite104 (Figs. 30, 31, 32). With increasing time at temperature, zircon will eventually convert partially or completely to ZrO2. Nearly all zircons observed on the surfaces of melted materials were either melted or showed some conversion to baddeleyite. We observed one zircon grain (Fig. 32d–e) displaying granular ZrO2 associated with three phases that span a wide range of SiO2 concentrations, likely formed at temperatures above 1687 °C. This extreme temperature and competing loss of SiO over an inferred duration of only several seconds led to complex microstructures, where grains melted, outgassed, and diffused into the surrounding matrix.Figure 31SEM images of other melted zircon grains in palace potsherd. (a) Two melted zircon grains adjacent to a previously discussed melted quartz grain; (b) close-up of same zircon grains; (c) manually constructed EDS-based phase map showing baddeleyite grains in green. The blue area represents melted zircon, while the red background represents the Ca–Al–Si matrix of the melted pottery. (d) Manually constructed EDS-based phase map of zircon grain showing small baddeleyite grains in green at the top.Full size imageFigure 32SEM images of melted zircon grains in mudbrick meltglass from the palace. (a) Thermally distorted zircon grain with a “hook” that resulted from the flow of molten material at  > 1687 °C; the darker area represents unrelated debris on top of zircon. (b) Manually constructed EDS-based phase map showing baddeleyite grains (Bd = ZrO2) in green, zircon in blue, and melted mudbrick in red. (c) Zircon grain showing limited thermal alteration, yet sufficient to cause dissociation into bright baddeleyite grains at ~ 1676 °C. (d) Zircon grain exhibiting three phases of thermal alteration, as shown in detail in (e), where a manually constructed EDS-based phase map demonstrates that high temperatures caused bubbling in the center band of zircon (purple = Hi) producing sub-micron-sized grains of baddeleyite (e.g., at arrow). Medium temperatures caused zircon to melt and flow (blue = Lo), and lower temperatures at the left end of grain produced thermal cracks (medium blue = Med). The green area marks the high-Si diffusion zone resulting from the dissociation of zircon. (f) Zircon grain from TeH has been fully converted to granular baddeleyite.Full size imageDiscussion of melted zirconZircon grains have a theoretical, equilibrium melting point of ~ 1687 °C. Under laboratory heating17, zircon grains showed no detectable alteration in shape at ~ 1300 °C but displayed incipient melting of grain edges and dissociation to baddeleyite beginning at ~ 1400 °C with increasing dissociation to 1500 °C17. Most zircon grains  120 µm were still recognizable but displayed considerable melting17. These experiments establish a lower melting range for TeH zircon grains of ~ 1400° to 1500 °C.Patterson105 showed that zircon dissociation becomes favorable above 1538 °C and particles between 1 and 100 µm in size melted and dissociated when passing through a plasma, forming spherules with various amounts of SiO2 glass containing ZrO2 crystallites ranging in size from 5 nm to 1 µm. The majority of zircon crystals were monoclinic, but tetragonal ZrO2 was observed for the smaller crystallite sizes. Residence times were in the order of 100 ms, and the specific ZrO2 to SiO2 ratio within each spherule depended on the particle’s time at temperature106.Bohor et al.104 presented images of impact-shocked zircons from the K-Pg impact event at 66 Ma that are morphologically indistinguishable from those at TeH. Decorated zircon grains are uncommon in nature but commonly associated with cosmic impact events, as evidenced by two partially melted zircons from the known airburst/impact at Dakhleh Oasis, Egypt (Fig. 30e). The presence of bubbles indicates that temperatures reached at least 1676 °C, where the zircon began to dissociate and outgas. Similar dissociated zircon grains also have been found in tektite glass and distal fallback ejecta (deposited from hot vapor clouds). Granular baddeleyite-zircon has been found in the ~ 150-km-wide K-Pg impact crater107 and the 28-km-wide Mistatin Lake crater in Canada107. The dissociation of zircon requires high temperatures of ~ 1676 °C104, implying that TeH was exposed to similar extreme conditions.Melted chromite grainsExamples of melted chromite, another mineral that melts at high temperatures, were also observed. Thermally-altered chromite grains were observed in melted pottery, melted mudbricks, and melted roofing clay from the palace. Their estimated density was 1 grain per 100 mm2, making them rarer than melted zircon grains. The morphologies of chromite grains range from thermally altered (Fig. 33a) to fully melted (Fig. 33b, d). One chromite grain from the palace displays unusual octahedral cleavage or shock-induced planar fractures (Fig. 33b). The typical chemical composition for chromite is 25.0 wt.% Fe, 28.6 wt.% O, and 46.5 wt.% Cr, although the Cr content can vary from low values to ~ 68 wt.%. SEM images reveal that, as chromite grains melted, some Cr-rich molten material migrated into and mixed with the host melt, causing an increase in Cr and Fe, and corresponding depletion of Si. The ratio of Cr to Fe in chromite affects its equilibrium melting point, which varies from ~ 1590 °C for a negligible amount of Cr up to ~ 2265 °C for ~ 46.5 wt.% Cr as in chromite or chromian magnetite ((Fe)Cr2O4), placing the melting point of TeH chromite at close to 2265 °C.Figure 33SEM images of melted chromite grains found on a melted potsherd from the palace. (a) Shattered, polycrystalline chromite grain that appears to have become agglutinated while molten. (b) Melted chromite grain, displaying cleavage (lamellae) suggestive of thermal and/or mechanical shock metamorphism at ~ 12 GPa; (c) close-up image showing angles between three sets of crystalline cleavage; (d) manually constructed EDS-based phase map showing chromite (purple) embedded in Ca–Al–Si matrix. The lines mark three sets of cleavage extending across the entire grain. A melt tail merging with the matrix is observed to trail off to the upper right of the grain at arrow.Full size imageDiscussion of melted chromiteChromite grains theoretically melt at ~ 2190 °C. Moore et al.17 reported the results of heating experiments in which chromite grains in bulk sediment showed almost no thermal alteration up to ~ 1500 °C (Supporting Information, Fig. S8). At temperatures of ~ 1600 °C and ~ 1700 °C, the shapes of chromite grains were intact but exhibited limited melting of grain edges. These results establish a range of ~ 1600° to 1700 °C for melting chromite grains.Because chromite typically does not exhibit cleavage, the grain exhibiting this feature is highly unusual. Its origin is unclear but there are several possibilities. The cleavage may have resulted from exsolution while cooling in the source magma. Alternately, the lamellae may have resulted from mechanical shock during a cosmic impact, under the same conditions that produced the shocked quartz, as reported by Chen et al.108 for meteorites shocked at pressures of ~ 12 GPa. Or they may have been formed by thermal shock, i.e., rapid thermal loading followed by rapid quenching. This latter suggestion is supported by the observation that the outside glass coating on the potsherd does not exhibit any quench crystals, implying that the cooling progressed very rapidly from liquid state to solid state (glass). This is rare in terrestrial events except for some varieties of obsidian, but common in melted material produced by atomic detonations (trinitite), lightning strikes (fulgurites), and cosmic airburst/impacts (meltglass)81. More investigations are needed to determine the origin of the potentially shocked chromite.Nuggets of Ir, Pt, Ru, Ni, Ag, Au, Cr, and Cu in meltglassUsing SEM–EDS, we investigated abundances and potential origins (terrestrial versus extraterrestrial) of platinum-group elements (PGEs) embedded in TeH meltglass, in addition to Ni, Au, and Ag. Samples studied include melted pottery (n = 3); melted mudbrick (n = 6); melted roofing clay (n = 1), and melted lime-based building plaster (n = 1). On the surfaces of all four types of meltglass, we observed melted metal-rich nuggets and irregularly shaped metallic splatter, some with high concentrations of PGEs (ruthenium (Ru), rhodium (Rh), palladium (Pd), osmium (Os), iridium (Ir), and platinum (Pt)) and some nuggets enriched in silver (Ag), gold (Au), chromium (Cr), copper (Cu), and nickel (Ni) with no PGEs (Figs. 34, 35). Importantly, these metal-rich nuggets were observed only on the top surfaces of meltglass and not inside vesicles or on broken interior surfaces.Figure 34SEM images of nuggets of melted metals in mudbrick meltglass from the palace. (a)–(c) Pt-dominant TeH nuggets enriched in ruthenium (Ru), rhodium (Rh), palladium (Pd), osmium (Os), iridium (Ir), and platinum (Pt). (d)–(f) Fe-dominant TeH splatter is also enriched in PGEs. (g)–(i) Nuggets enriched in varying percentages and combinations of nickel (Ni), chromium (Cr), copper (Cu), and silver (Ag).Full size imageFigure 35Average composition of selected metal-rich nuggets from the palace. (a-h) Silver (Ag), gold (Au), chromium (Cr), copper (Cu), iridium (Ir), nickel (Ni), platinum (Pt), and ruthenium (Ru), showing wt.% in selected nuggets from the destruction layer of the palace (7GG).Full size imageUsing SEM–EDS, we identified variable concentrations and assemblages of PGEs. The metallic particles appear to have melted at high temperatures based on the minimum melting points of the elements: iridium at 2466 °C; platinum = 1768 °C; and ruthenium = 2334 °C, indicating a temperature range of between approximately 1768° and 2466 °C. Our investigations also identified two PGE groups, one with nuggets in which Pt dominates Fe and the other with metallic splatter in which Fe dominates Pt.Pt-dominant nuggetsWe conducted 21 measurements on Pt-dominant TeH nuggets on meltglass (Fig. 34a–c). The nuggets average ~ 5 µm in length (range 1–12 µm) with an estimated concentration of 1 nugget per 10 mm2. For these nuggets, Fe concentrations average 1.0 wt.%, Ir = 6.0 wt.%, and Pt = 44.9 wt.% (Supporting Information, Tables S6, S7). The presence of PGEs was confirmed by two SEM–EDS instruments that verified the accurate identification of PGEs through analyses of several blanks that showed no PGE content. Some concentrations are low ( Pt or Pt  > Fe were found to be consistent between the two instruments.To determine the source of TeH nuggets and splatter, we constructed ternary diagrams. Terrestrial PGE nuggets are commonly found in ore bodies that when eroded, can become concentrated in riverine placer deposits, including those of the Jordan River floodplain. To compare Fe–Ir–Pt relationships among the TeH nuggets, we compiled data from nearby placer deposits in Greece109, Turkey110,111, and Iraq112, along with distant placers in Russia113,114,115, Canada116, and Alaska, USA117,118. The compilation of 109 Pt-dominant placer nuggets indicates that the average Fe concentration is 8.2 wt.%, Ir = 2.9 wt.%, and Pt = 80.3 wt.%. For the Ir-dominant placer nuggets (n = 104), Fe = 0.4 wt.%, Ir = 47.8 wt.%, and Pt = 5.3 wt.% (Supporting Information, Tables S6, S7). The ternary diagrams reveal that the values for Pt-dominant TeH nuggets overlap with Pt-dominant terrestrial placer nuggets but the Fe-dominant splatter is dissimilar (Fig. 36a).Figure 36Ternary diagrams for PGE-rich grains. Comparison of Fe–Ir–Pt ratios of PGE-rich nuggets fused into the surfaces of TeH meltglass. There are two populations of TeH nuggets (red diamonds): Pt-dominant at #1 (top) and Fe-dominant at #2 (bottom left). (a) TeH Pt-dominant nugget group #1 (red diamonds) overlaps Pt-dominant but not Ir-dominant nuggets (blue circles) from placers and ophiolite deposits in Greece, Turkey, Iraq, Russia, Canada, and the USA. The Fe-dominant TeH nugget group #2 is geochemically dissimilar to all known placer nuggets, suggesting that these nuggets are not placer-derived. (b) TeH nuggets (red diamonds) compared to nuggets in carbonaceous chondrites (light gray circles) and nuggets in cosmic spherules (dark gray circles). Pt-dominant TeH nuggets in group #1 are a poor match, but Fe-dominant TeH splatter is an excellent match with chondritic meteorites and cosmic spherules, suggesting that they may be extraterrestrial in origin and that the impactor may have been a chondrite. (c) TeH nuggets (red diamonds) are a poor match for most nuggets in iron meteorites (purple circles), but an excellent match for nuggets found in comets (green circles). These data suggest that Fe-dominant PGE nuggets at TeH may have originated from cometary material. (d) Semi-log comparison of PGEs ruthenium (Ru), rhodium (Rh), palladium (Pd), osmium (Os), iridium (Ir), and platinum (Pt), normalized to CI chondrites. TeH Fe-dominant splatter (red line) is an excellent match for PGE nuggets in carbonaceous chondrites (blue line), cosmic spherules (purple line), micrometeorites (dark blue line), and iron meteorites (gray line). In contrast, TeH PGE nuggets are a poor match for bulk material from CI-normalized CV-type chondrites (e.g., Allende; orange line) and CM-type chondrites (e.g., Murchison; brown line).Full size imageFe-dominant splatterWe made 8 measurements on TeH Fe-dominant PGE splatter (Fig. 34d–f). The metal-rich areas average ~ 318 µm in length (range 20–825 µm) with an estimated concentration of 1 PGE-rich bleb per mm2, 100× more common than the TeH nuggets. Average concentrations are Fe = 17.5 wt.%, Ir = 4.7 wt.%, and Pt = 1.5 wt.%.We explored a potential extraterrestrial origin by constructing ternary diagrams for comparison of TeH Fe-dominant splatter with known meteorites and comets (Fig. 36b, c). We compiled data for 164 nuggets extracted from carbonaceous chondritic meteorites (e.g., Allende, Murchison, Leoville, and Adelaide)119,120,121,122, seafloor cosmic spherules123,124, iron meteorites122,125, Comet Wild 2126, and cometary dust particles126. For average weight percentages, see Supporting Information, Tables S6, S7. The Fe-dominant TeH splatter (Fig. 36b) closely matches nuggets from carbonaceous chondrites and cosmic spherules but is a weak match for most iron meteorites (Fig. 36c). In addition, the TeH nuggets are similar to four cometary particles, two of which were collected during the Stardust flyby mission of Comet Wild 2 in 2004126. For average weight percentages, see Supporting Information, Tables S6, S7.To further explore an extraterrestrial connection for TeH Fe-dominant splatter, we compiled wt.% data for TeH PGEs (Rh, Ru, Pd, Os, Ir, and Pt) and normalized them to CI chondrites using values from Anders and Grevasse127. We compared those values to CI-normalized nuggets in carbonaceous chondrites, including CV-type chondrites (e.g., Allende) and CM types (e.g., Murchison)119,120,122,128,129,130,131, seafloor cosmic spherules124, micrometeorites123, and iron meteorites122,125. These results are shown in Fig. 36d.The TeH Fe-dominant splatter closely matches all types of extraterrestrial material with a similar pattern among all data sets: Pd has the lowest normalized values and Os and/or Ir have the highest, closely followed by Pt. The TeH splatter was also compared to the CI-normalized wt.% of bulk meteoritic material from CV- and CM-type chondrites (Fig. 36d). The composition of TeH splatter shows poor correlation with bulk chondritic materials, although the splatter is an excellent geochemical match with the PGE nuggets inside them. In summary, the CI normalization of PGEs suggests an extraterrestrial origin for the Fe-dominant TeH splatter, just as the ternary diagrams also suggest an extraterrestrial source. The correspondence of these two independent results suggests that the quantification of PGEs is sufficiently accurate in this study.Another unusually abundant element, Mo, is also associated with Fe-dominant splatter but not with Pt-dominant nuggets. Mo averages 0.3 wt.% with up to 1.1 wt.% detected in Fe-dominant splatter but with none detected in TeH Pt-dominant nuggets. Mo also is not reported in any terrestrial placer nuggets and occurs in low concentrations (less than ~ 0.02 wt.%) in iron meteorites. In contrast, Mo is reported at high concentrations in PGE nuggets from carbonaceous chondrites (~ 11.5 wt.%), cosmic spherules (0.6 wt.%), and cometary material (5.8 wt.%). Thus, the Mo content of TeH splatter appears dissimilar to terrestrial material but overlaps values of known cosmic material, suggesting an extraterrestrial origin.Based on the volume and weight of the meltglass, we estimate that the extraterrestrial-like metallic TeH Fe-dominant splatter represents  More

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Insects and virusOryctes rhinoceros was collected from Amami, Kagoshima, Japan in 2017 and Ishigaki, Okinawa, Japan in 2018. The insects were brought back to the lab in Tokyo and maintained in a moisture mushroom mat substrate (Mushroom Mat, Tsukiyono Kinokoen, Japan) which was also served as food for larvae. The temperature was held at 25–30 °C with a 16-h light / 8-h dark photoperiod. To collect eggs, 2 or 3 female adults were put in a plastic case containing a moisture mushroom mat substrate with a male adult beetle. The insect jelly (Dorcus Jelly, Fujikon, Japan) was provided ad libitum as food for adults. After 2 weeks, we collected eggs, and about 10 eggs were placed in a plastic cup with a moisture mushroom mat substrate until hatched larvae developed to the second instar. This strain was used in all bioassays in this study. All Japanese O. rhinoceros were confirmed as CRB-G.The OrNV-X2B isolate used in this study was originally isolated from Philippine CRB and obtained from AgResearch in New Zealand.Cell culturesFRI-AnCu-35 (AnCu35) cells were obtained from Genebank of NARO (Tsukuba, Japan)27. This continuous cell line was developed from embryos of the cupreous chafer, Anomala cuprea (Coleptera: Scarabaeidae). The cells were maintained as adherent cultures in 25 cm2 tissue culture flasks (Falcon, Corning, USA) at 25 °C in 5 ml of 10% Fetal Bovine Serum (Gibco, Thermo Fisher Scientific, USA) supplemented Grace’s insect medium (Gibco). Cells were passaged in the above culture medium until the cell monolayer reached 70% confluence.DNA extraction and identification of haplotypes in Palauan populationCRB specimens were collected in Palau using pheromone traps containing ethyl 4-methyloctanoate (ChemTica Internacional, Costa Rica). Adults were dissected to collect midgut and gut tissues to avoid cross contamination between dissection of individuals, which were immediately soaked into 0.1 μg/ml gentamicin solution to prevent bacterial contamination during transportation at room temperature. Specimens were stored at − 30 °C after arrival to Tokyo. The tissues were homogenized in cell lysis solution (10 mM Tris–HCl, 100 mM EDTA, 1% SDS, pH 8.0) using pestles in 1.5 ml microcentrifuge tubes. Homogenates were centrifuged at 12,000× g for 5 min at 4 °C. Proteinase K (200 µg/ml final concentration) (Nippon Gene Co. Ltd., Japan) was added to the supernatant and incubated at 50 °C for 5 h. To remove contaminating RNA, RNase A solution (100 µg/ml final concentration) (Nippon Gene Co. Ltd.) was added. After a 30 min incubation at 37 °C, the mixture was placed on ice and supplemented with 200 μl of Protein Precipitation Solution (Qiagen, Germany), and then centrifuged at 17,000× g for 15 min at 4 °C. The supernatant was isopropanol-precipitated, pelleted by centrifugation, and washed with 70% ethanol. Finally, precipitated DNA was dissolved in distilled MilliQ water. The concentrations of each DNA solution were measured by using NanoVue Plus (GE Healthcare, Buckinghamshire, England, UK). The sample DNA was diluted to 10 ng/μl and used for PCR. The following primer pair was used to amplify a 523 bp fragment of the COI gene: C1-J-1718Oryctes (5′-GGAGGTTTCGGAAATTGACTTGTTCC-3′) and C1-N-2191Oryctes (5′-CCAGGTAGAATTAAAATRTATACCTC-3′)9. Each 10 μl PCR reaction contained: 5 μl Emerald Amp (Takara, Japan), 0.3 μl forward primer (10 μM), 0.3 μl reverse primer (10 μM), 3.4 μl Milli-Q water (Merck Millipore, USA), and 1 µl template DNA. PCR amplifications were performed in a Life ECO thermocycler (Bioer Technology, China) with a cycling profile of 35 cycles of 94 °C denaturation (30 s), 50 °C annealing (45 s), 72 °C extension (1 min) with an initial denaturation of 3 min at 94 °C and a final extension of 5 min at 72 °C. A 5 μl aliquot of each PCR amplicon was checked by agarose gel electrophoresis (1.5%, 1 × TBE), stained with Midori green (Nippon Genetics, Japan) and fluorescence visualized over UV light. Photographs were recorded using an E-BOX-VX2 /20 M (E & M, Japan).For direct sequencing, the PCR products were purified using a QIAquick PCR Purification Kit (Qiagen). The purified DNA was sequenced using BigDye Terminator Kit ver. 3.1 (Applied Biosystems, USA) and performed by the 3700 DNA analyzer (Applied Biosystems). The obtained sequences were analyzed using MEGA X software28 and the G haplotype was identified by the presence of the (A→G) point mutation in the COI region as previously described9.Virus detection in Palauan populationUsing the same samples as above, virus detection was carried out by PCR. The following primer pair was used to amplify a 944 bp fragment of the OrNV-gp054 gene (GrBNV-gp83-like protein): OrNV15a (5′-ATTACGTCGTAGAGGCAATC-3′) and OrNV15b (5′-ATGATCGATTCGTCTATGG-3′)29. PCR amplifications were performed as above.Transmission electron microscopy (TEM) was also used for detection of OrNV within a subset of PCR positive CRB tissue samples. After washing in phosphate-buffered saline (PBS), midgut and fat body samples of Palauan CRB adults from Melekeok and Aimeliik (respectively; two each), were subjected to following resin fixation as described previously30: tissues were fixed in 5% glutaraldehyde for 1 h, rinsed 4 times with Millonig’s phosphate buffer (0.18% NaH2PO4 × H2O, 2.33% Na2HPO4 × 7H2O, 0.5% NaCl, pH 7.4), post-fixed and stained in 1% OsO4 for 2 h and dehydrated in an ethanol series. Following the final dehydration step, the ethanol was replaced by QY-1 (Nisshin EM, Tokyo), and the tissues were embedded in epoxy resin comprising 47% TAAB EPON812, 19% DDSA, 32% MNA and 2% DMP30 (Nisshin EM, Tokyo). Then, they were cut into 70 nm thick sections with a diamond knife on an Ultracut N ultramicrotome (Leica, Vienna, Austria), attached to grids and observed using TEM (JEM-1400Plus, JEOL, Japan).Isolation of OrNV from Palauan samples and infectivity to Japanese CRB larvaeVirus isolation was carried out using a modification of a method previously described23. The frozen tissues of two virus positive CRB-G from Melekeok were washed with PBS twice, and after grounding with 1 ml PBS by pestles, centrifuged at 6,000 g × 5 min at 4 °C. The supernatant was filtered by 0.45 µm pore sized filter (Merck, USA) and transferred to a 1.5 ml ultracentrifuge tube in a clean bench. Virus was pelleted by centrifugation at 4 °C, 98,600 g for 30 min using a TLA55 rotor. After separation, the supernatant was discarded and the pellet was suspended in 500 μl of PBS and designated as “virus solution”. A portion of this solution (30 µl/larva) was intrahemocoelically injected into 82nd instar CRB to evaluate its infectivity. This experiment had no biological replicates due to the very small amount of inoculum available. Intrahemocoelically injected larvae were reared in the insect rearing mat at 25 °C for two weeks. Following death, larval cadavers were immediately dissected to collect midgut for following RNA extraction to detect expression of a viral gene, and electron microscopy observation. Total RNA was extracted from larval tissue samples using ISOGEN (Nippon Gene Co. Ltd., Tokyo, Japan), as described in the manufactural protocol. The total RNA samples were treated with RNAse-free recombinant DNAse I (TaKaRa, Japan) to remove the contaminating DNAs. The DNAse I treated total RNA samples (approximately 100 ng/µl) were used as templates for cDNA synthesis using a TaKaRa RNA PCR Kit (AMV) ver. 3.0 (TaKaRa, Japan). PCR reactions were conducted as above using OrNV15a and b primers (detects gene GrBNV-gp83-like gene). This experiment was conducted in triplicate.Inoculum preparation using FRI-AnCu-35 cellsOrNV isolates were propagated using the FRI-AnCu-35 (AnCu35) cell line for further analyses following methods previously described for the DSIR-Ha-1179 cell line system9,12. AnCu35 was a Coleopteran cell line readily available in Japan, and was inoculated with the Palau OrNV solution prepared above and the OrNV-X2B isolate which was provided by AgResearch, New Zealand. When the cell culture reached 25% confluency, a 100 µl aliquot of virus solution was inoculated and incubated at 25 °C. The virus-treated cells were observed by optical microscope.Quantification of viral copy number using qPCR was conducted as follows. To measure the amount of OrNV virus produced by the AnCu35 cell line, DNA was extracted as described above for tissue samples from 1.5 ml of the virus treated cell’s suspension at 10 dpi (3 suspensions per each virus isolate). The extracted DNA was subjected to quantitative PCR (qPCR) following previously described methods31. The primer pair for qPCR was designed from the genome sequence of the P74 homolog of OrNV, a viral structural protein that is conserved widely among nudiviruses, polydnaviruses and baculoviruses32, to amplify a region of 82 bp of OrNV-X2B-gp120 (OrNV-p74_f2026: 5′-ATCGCCGGTGTGTTTATGG-3′, OrNV-p74_r2107: 5′-AGAGGGCTAACGCTACGAC-3′). The qPCR reaction was performed by using Step One Plus Real-Time PCR System (Life Technologies, USA). The reaction mixture contained 10 ng of template DNA, 5 µl of FastStart Universal SYBR Green Master Mix (ROX) (Roche, Switzerland), 0.3 µl forward primer (10 µM), 0.3 µl reverse primer (10 µM), and 3.4 µl Milli-Q water. The qPCR cycle condition was as follows: 95 °C 10 min; 40 cycle of 95 °C 15 s, 60 °C 1 min. At the end of the cycles, a dissociation curve analysis of the amplified product was performed as follows: 95 °C 15 s, 60 °C 1 min, 95 °C 15 s. The Ct value of each sample DNA was measured twice using two wells as technical replicates. The quantity of the viral genome (ng) in each sample was calculated from a standard curve generated from 29.7 to 29.7 × 10–5 ng of purified PCR amplicon from the OrNV P74 gene. The viral copies in 1 ng of sample DNA was estimated from the molecular weight of qPCR target region (p74). The virus titer was determined from average copy numbers of three virus suspensions as follows. The p74 qPCR amplicon was 83 bp, and the molecular weight of the amplicon was calculated as the length of dsDNA (83 bp) × 330 daltons × 2 nt/bp = 54,780 daltons (g/mol). DNA weight of 1 copy of virus genome was calculated as 54,780 g/mol/Avogadro constant (6.023 × 1023 molecules/mol) = 9.095 × 10–20 g/ molecule. Amplicons of the above region was purified by QIA quick PCR purification kit (Qiagen) and 29.7 ng/ul of DNA was obtained for use as a quantification standard. This is equivalent to 3.266 × 1011 copies of p74 gene (because the amplicon is 9.095 × 10–20 g/copy). Based on qPCR using the serial dilutions (× 10 – 105) of the standard DNA prepared above, Ct values were examined by each concentration of viral DNA. Ct-value = − 3.3112x – 1.4219 (x: diluton factor of 10x). Accordingly, copy number of p74 = 3.266 × 1011+x. Viral copy number (copy number of p74 genes) was calculated from Ct-value from the above formula.Viral replication in CRB larvae by time course and killing speedField collected CRB-G larvae from Japan were inoculated with the OrNV-Palau1 and -X2B isolates to examine establishment of infection over time using qPCR. The inoculum was prepared from supernatant collected from OrNV infected AnCu35 cell cultures at 10 dpi, passed through a 0.45 µm filter, and preserved at 4 °C until use.Second instar CRB was inoculated intrahemocoelically with 30 μl of the virus solution prepared from cell-culture per larva using a microinjector (Kiya Kogyo Seisakusho, Japan) fitted with a micro-syringe (Ito Seisakusho, Japan). The virus doses of OrNV-Palau1 and -X2B strains used for inoculation were confirmed to be comparable by absolute quantification using the above qPCR method (Palau1: 3.1 × 105 copies/ng, X2B: 3.3 × 105copies/ng; the mean titer of 3 DNA templates, respectively). As a mock treatment, CRB was injected with 30 µl PBS. The inoculated larvae were kept individually in plastic containers with a rearing mat in a 25 °C incubator. The samples were collected at 3, 6, and 9 dpi (25–30 larvae per time point) into 15 ml tubes and stored at − 30 °C until the DNA was extracted as above. Total DNA was extracted from whole, individual larvae which were dissected to remove midgut contents to prevent interference to Taq polymerase, and subjected to qPCR as above. Changes in viral copy number within the same virus strain over time were analyzed by one-way, nonparametric Steel–Dwass tests using JMP@ 9.0.0 software (SAS Institute, Cary, NC). Differences in virus copy number between strains were analyzed in the same way, but to correct for errors in the test values due to multiple comparisons, Bonferroni’s correction was used to set the α-value for the test at 0.008333. Ten larvae were inoculated and examined per each treatment-time point with three replications.To estimate killing speed, CRB-G larvae from Japan were inoculated with the OrNV-Palau1 and -X2B isolates as described previously. Intrahemocoelically inoculated larvae were reared individually in plastic containers with a rearing mat in a 25 °C incubator. Mortality of inoculated larvae were observed every day. Forty larvae were examined in a replicate with three replications carried out for virus treatments (total 120 larvae). The mock PBS inoculation treatment was done only once (total 37 larvae).Genome sequencingGenome sequencing of the OrNV-Palau1 isolate and X2B isolate was conducted. For obtaining high quality DNA, virus particles were purified, from 3 mL of AnCu35 culture supernatant collected six days after inoculation with OrNV. Virus containing supernatant was transferred to Ultra-Clear polyallomer tubes (Beckman Coulter, USA) with a 20–50% (w/w) sucrose density gradient and subjected to ultracentrifugation at 72,100 g, 4 °C, for 1 h. After ultracentrifugation, the white virus band was collected in a 1.5 ml tube. The solution was then subjected to ultracentrifugation at 110,000 g, 4 °C for 1 h to precipitate the viral particles33. Then, DNA was extracted from purified OrNV virions as described above. For the sequencing analysis, DNA libraries were prepared using the Nextera XT DNA Library Prep Kit (Illumina, USA). Amplified libraries were sequenced on Illumina HiSeq 2500 instrument using paired-end 2 × 150 bp chemistry which was performed by Novogene (Beijing, China). Contigs of each strain from NGS reads were generated by assembly using Unicycler (version 0.4.8)34. The gaps between contigs were further closed with Sanger sequences obtained by PCR direct sequencing using appropriate specific primers, and the sequence was aligned by minimap2 (version 2.17)35. The assembly and sequences of contigs were also confirmed by mapping to the OrNV isolate Solomon Islands genome sequence (GenBank accession no. MN623374.1) with NGS reads and Sanger sequences using minimap2. The mapped reads (SAM files) were converted to BAM format using SAMtools (version 1.10)36. After the sorting and indexing of BAM files, the consensus sequences were generated using bcftools (version 1.10.2)37.ORFs of at least 50 codons in size that possessed significant amino acid sequence similarity with ORFs from OrNV-Ma07 were identified with Lasergene GeneQuest (DNAStar, v. 17) and BLASTp. ORFs with no significant matches to other sequences also were selected for annotation if (a) they did not overlap a larger ORF by  > 75 bp, and (b) they were predicted to be protein-encoding by both the fgenesV0 (http://www.softberry.com/berry.phtml?topic=index&group=programs&subgroup=gfindv) and Vgas38 programs.OrNV genome sequences were compared by pairwise alignment using the Martinez/Needleman-Wunsch method as implemented in Lasergene MegAlign 15. Pairwise sequence identities were determined from these alignments as previously described39. Differences in ORF content and distribution of selected OrNV genomic regions were visualized with Mauve version 2015022640.Phylogenetic inferenceTo infer the relationships among OrNV isolates on the basis of nucleotide sequence alignments, the DNA polymerase ORFs of completely sequenced isolates (Table 2), OrNV-PV50516, and a set of nine isolates from Indonesia17 were aligned by MUSCLE as implemented in Lasergene MegAlign Pro v. 17 (DNAStar). Phylogeny was inferred by maximum likelihood using MEGA X28 with the Tamura-Nei (TN93) model41, with ambiguous data eliminated prior to analysis. Tree reliability was evaluated by bootstrap with 500 replicates. More

This dataset relies on two types of technical validation: ensuring the accuracy of (1) project attributes and, where applicable, (2) their geographic locations.Project attribute validation: the double-verification methodExisting sources for Chinese overseas development finance rely on a variety of verification standards. The present dataset extends the most stringent approach of the existing “double verification” methods pioneered by the China Africa Research Initiative at the Johns Hopkins University School of Advanced International Studies (SAIS-CARI) to create a harmonized, global standard.The double verification method is based on academic literature showing a tendency to overstate, rather than understate, finance commitments. For example, Ebeke and Ölçer49 show that major infrastructure projects are often timed for announcements to coincide with political campaigns. Regional case studies9,50 show patterns of planners avoiding the publication of projects’ environmental and social risks, but simultaneously maximizing the visibility of the projects and their financial commitments, often before they are finalized. For this reason, earlier datasets have struggled to correctly identify and exclude projects that have been publicized but never materialized, resulting in sometimes significant over-estimations51.The possibility remains of under-counting. As Horn, Reinhart, and Trebesch (2019)15 point out, in reference to “hidden” Chinese finance, many overseas Chinese loans are never fully disclosed. For this reason, we cast the widest possible net for financing commitments and then narrowing those findings by applying the standard of double-verification. It is for this reason also that we perform annual updates, and in each update include previous years’ data, in order to include any additional projects that may not have been disclosed until a much later date.Our aim is to provide the most evidence-based supported data in order to have a more empirical based understanding of Chinese overseas development finance. Erring on the side of caution then, double verification is admittedly a more conservative set of estimates but grants all scholars and stakeholders the confidence that every record in the dataset does indeed exist.Without public reporting by CDB and ExImBank of their lending operations, we are limited to reporting by government (and government-affiliated) sources, academic, civil society, and press reports. The system of double verification ensures accuracy in this context, requiring agreement on the core characteristics of each loan agreement between at least one Chinese source and at least one international source.For China-side verification, we rely on official and quasi-official sources associated with the Chinese government or Chinese Communist Party. We include the following sources:

1.

Chinese government and DFI websites (including CDB.com.cn, ExImBank.gov.cn, and any other source with a domain ending in .gov.cn)

2.

Websites of Chinese embassies abroad

3.

Chinese government or CCP-affiliated press sites:

a.

China Daily, http://www.chinadaily.com.cn

b.

China Global Television Network, https://www.cgtn.com

c.

China News, http://www.chinanews.com

d.

China Plus, http://chinaplus.cri.cn

e.

Guangming Daily, http://www.gmw.cn

f.

People, http://www.people.cn

g.

Xinhua, http://www.xinhuanet.com

For international verification, we rely similarly on government reports, supplemented with academic, civil society, and private press reports. As mentioned above, when differences emerge among sources, we resolve these conflicts by giving government sources top priority, followed by academic sources, civil society sources, and private press sources. Government press sources, such as the Chinese sources listed above, are given the weight of government sources. This method coincides with that of other datasets with double verification7,8,21.Because of the stringency of the double-verification standard used here, we exclude the smallest finance agreements (those below $25 million USD). Excluding these low-level loans necessarily involves a small degree of under-counting. For example, Brautigam et al. (2020)8 show that loans of less than $25 million each comprise just $389 million in total commitments, out of a total of $148 billion in financing commitments by CDB and ExImBank between 2008 and 2018 in Africa: approximately 0.2% of the total. However, including these loans would introduce significant geographic bias toward countries with particularly transparent governments and open media environments. As the purpose of the present effort is to enable more reliable geospatial analysis, the inclusion of this additional activity was not deemed worthy of the cost to the reliability of analysis using it.It is worth comparing these results to those of other datasets for context. Among other independent datasets of Chinese lending, only AidData11,12 and Horn, Reinhart, and Trebesch15 have global coverage, and of those two, only AidData differentiates by lender, allowing a strict comparison. As Fig. 1 shows, AidData includes $463 billion in policy bank loans between 2008 and 2014 that would meet the standard for inclusion in the present dataset if they could be validated. However, in that same time period, our methodology found that only $271 billion of loans could pass the validation standards introduced here.This process of double-verification results in a dataset that excludes some countries that appear in other datasets. For example, in the case of four countries, this process resulted in the present dataset having no loans listed, even though CDB and/or ExImBank loans appear in AidData, the largest global dataset, with loans that would qualify for inclusion here if they could be validated. Those four are: Central African Republic (for which we were unable to find doubly verified validation for the Boali No. 3 hydropower plant project), Dominica (for which we were unable to double verify the source of the loan for rehabilitation of State College), Turkey (whose Turk Telecom was privatized before the loan listed in AidData), and Yemen (for which we were unable to find Chinese validation for the Bajal cement factory project). In addition to these four countries, three others are included in AidData but with no loans of $25 million or more: Burundi, Colombia, and Sierra Leone.As with other researchers in this space7,8,21 we understand that individual projects within such funds can be hidden from public view until the line of credit or framework agreement is renewed or laid down unused. Thus, we include such financing agreements when they are initially drawn up, but then withdraw them from subsequent updates if it comes to light that they were unused. If they are renewed, as lines of credit frequently are, such renewals do not represent new financing but simply a relaxation of the time period for use of the original commitment. For this reason, renewals are not considered separately.Finally, not all projects in this dataset have been completed as of this writing. We have removed all projects that have been publicly cancelled, but ongoing projects with active financing commitments remain, even if construction has not yet begun or has been suspended. For this reason, we refer to each observation as a commitment or agreement, rather than a loan. Funds may or may not have been disbursed as of this writing, but commitments have been made and remain valid. In all, this double-verification process resulted in a final dataset of 857 finance commitments in 93 countries from 2008 through 2019.Location validationOf the 857 finance commitments in the final dataset, 664 have a geographic footprint of some type. These projects – encompassing agriculture, extraction, manufacturing, utilities, infrastructure, and other installations – were located according to the following procedure.Several of the existing datasets listed above include the location of financed projects: AidData, CSIS, Dayant and Pryke, and the World Bank11,13,14,26. Among these datasets, CSIS’ Reconnecting Asia merits special mention, as it displays project locations through embedded Google Maps. For projects originating in this dataset, we queried CSIS for the coordinates in these maps (using code available in R as CSIS_to_coord_str.R on the project repository). For these observations, we used these reported locations as initial estimates, to be visually validated thereafter. For energy projects not listed in these project datasets, we used the following sources for initial estimates of project locations:

Power plants: Global Power Plant Database52.

Coal-fired power plants: Global Energy Monitor53

Fossil fuel pipelines and related infrastructure: Global Fossil Infrastructure Tracker54

For other observations, we developed an API to query Google Maps for the locations of each (available in R as GoogleMaps_OSM_API_query.R on the OSF project repository).For all observations – those included in previous geolocated datasets, those located through querying Google Maps and Open Street Maps, and those with no query response – we validated the locations visually through the use of Google Maps, Open Street Maps, and Open Route Services, as shown in Fig. 3 below.Fig. 3Examples of point, line, and polygon footprints. Left to right: Rehabilitation of Sam Lord’s Castle, Barbados; Soyo-Kapary Electrical Transmission and Transformation Project, Angola; Kirirom III hydropower plant (reservoir), Cambodia.Full size imageThis process represents a significant elevation of requirement needing to be met for projects to be reported as having a precise location, in comparison to previous geocoded datasets. For example, AidData allows projects to be reported at the most precise location category based on the precise boundaries of an area of uncertainty around a project—including populated places or the political seats of geographic areas—rather than the precise point or boundaries of the true project site(s). The resulting high-precision category includes 579 sovereign finance commitments by CDB and ExImBank identified by AidData during our period of study, of which only 105 geotags are associated with specific sites of projects. The remaining projects’ location are defined by the administrative division or the political seats thereof. This is in contrast to the more stringent precision classification scheme in our dataset. Projects marked with a precision code of “1” in the present dataset have all been visually located as site-specific project footprints. The introduction of this new level of precision allows for linear and polygonal projects to be represented with their complete footprints, rather than representative points, which enables a more thorough analysis of environmental risks and impacts, including for example, the impacts of the entire length of a highway or the entire area of a mine. Analysts using this dataset will be able to avoid the under-estimation of environmental impacts necessarily introduced by relying on representative points. Our first such analysis uses these precise footprints to compare location-based social and ecological risks of Chinese overseas development finance to World Bank projects, based on their proximity to the boundaries of national protected areas, possible critical habitats, and indigenous territories48. The dataset also supports holistic environmental analysis of interconnected networks of projects, based on their collective footprints. Yang et al (2021) use these collective footprints to examine the environmental and social sensitivity of Chinese overseas development finance locations, and find that the total footprint is significantly concentrated in more sensitive territory than World Bank projects during the same time period55.To accurately reflect the variety of types of footprints across various types of finance projects, we classified each geolocated observation as a point (or collection of points), line (or collection of discontinuous lines), or polygon (or collection of discontinuous polygons). Points are used for individual buildings or installations. Lines are used for linear infrastructure including roads, rails, power distribution, wired communications networks, and pipelines. Polygons show projects with footprints that are larger than single buildings or installations, with well-defined boundaries, including dam reservoirs, oil and gas fields, and clusters of buildings such as housing or stadium complexes. The distribution of projects among footprint types is listed in Table 4.Table 4 Footprint types.Full size tableA few examples merit further explanation regarding their classification of footprint type. First, wind farms are comprised of turbines along access roads; to accurately show the total geographic footprints, we show them as linear infrastructure comprised of their access roads. In addition, projects with lower levels of geographic precision (at the national level or first/second-level administrative division level) are shown as polygons that encompass these areas, showing the municipal, provincial, or national boundaries48. More

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