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Phylogenetic analysesA total of 21 sequences were newly generated and deposited in GenBank (Supplementary Table 1). The concatenated sequence alignment of the three loci comprised 100 sequences (38 for ITS, 30 for rpb2 and 32 for mtSSU) from 43 collections (Supplementary Table 1). The alignment was 2,004 characters long, including gaps. Multi-locus trees generated from ML and BI analyses showed similar topologies without any supported topological conflict. The multi-locus phylogeny (Fig. 1) confirmed placement of all Thai collections within the well-supported R. subsect. Amoeninae (ML = 99, BI = 1.0). Five collections from northeastern Thailand and two collections from northern Thailand form two strongly supported clades and are described below as the new species R. bellissima sp. nov. and R. luteonana sp. nov. The new species are not resolved as sister. The first species, R. bellissima, is strongly supported as sister to a clade of Australian sequestrate species that includes R. variispora T. Lebel and an undescribed Russula sp. labeled as Macowanites sp. The Indian species R. intervenosa S. Paloi, A.K. Dutta & K. Acharya is placed as sister to them with bootstrap support of 77. The second species, R. luteonana, is placed with moderate support as sister to the sequestrate European species R. andaluciana T.F. Elliott & Trappe.Figure 1ML phylogenetic tree inferred from the three-gene dataset (ITS, rpb2, mtSSU) of Russula subsection Amoeninae species, using ML and BI analyses. Three members of R. subg. Heterophyllidiae are used as outgroup. Species in boldface are new species in this study. Bootstrap support values (BS ≥ 50%) and posterior probabilities (PP ≥ 0.90) are shown at the supported branches.Full size imageThe ITS tree (Fig. 2) shows a similar topology and relationships for the studied specimens. In addition, R. intervenosa received good support (ML = 84, BI = 0.99) as sister to the clade of R. bellissima and R. variispora. Five additional ITS sequences that are grouped with strong support within R. bellissima species clade were recovered, three from Thailand, one from Laos, and one from Singapore. We did not recover any other Amoeninae ITS sequences from Thailand.Figure 2ML phylogenetic tree inferred from the ITS region of Russula subsection Amoeninae species and allied groups, using ML and BI methods. Samples in boldface are new species in this study. Bootstrap support values (BS ≥ 50%) and posterior probabilities (PP ≥ 0.90) are shown at the supported branches.Full size imageTaxonomy
Russula bellissima Manz & F. Hampe sp. nov.
Mycobank: MB 840549Holotype THAILAND, Theong district, Chiang Rai, 19°36′45”N 100°4′00”E, alt. 500 m, dry dipterocarpus forest in small groups on loamy soil, 12 July 2012, F. Hampe (Holotype: GENT FH 12-127; Isotype: MFLU12-0619).Etymology ’bellus’ = latin for beautiful, pretty, lovely; ’bellissima’ = the most beautiful. Resembling the species Russula bella which is also belonging to Russula subsection Amoeninae.Diagnosis Pileus small to medium-sized; cuticle dry, smooth, matt and pruinose, red; stipe white or with a red flush; spore ornamentation of moderately distant to dense amyloid spines or warts, frequently fused into short crests or even long wings; suprahilar spot inamyloid; hymenial cystidia and pileocystidia absent.Pileus (Fig. 3) small to medium sized, 10–50 mm diam., young hemispherical or convex, becoming plane and depressed at the centre; margin first even, when old distinctly tuberculate-striate up to 10 mm from the margin, often radially cracking; cuticle hardly peeling, radially disrupted into small patches, pruinose when young, later dry, smooth, matt and pruinose in the centre, colour near the margin when young varnish red (9C8), later red to coral red (9B6-7); near the centre deep red, blood red, dark red (10C7-8), raspberry red (10D7), strawberry red (10D8) or purple brown (10E-F8). Lamellae: 3–5 mm deep, thin, moderately dense, 6–8 at 1 cm near the pileus margin, adnexed, white, slightly anastomosing at the base; lamellulae absent, occasionally forked near the stipe; edges concolorous, entire but pruinose under lens. Stipe: 10–30 × 3–7 mm, usually narrowed towards the base, sometimes cylindrical, surface smooth, white and mainly with a distinct pastel red to red flush, occasionally completely white or sometimes also almost completely red, interior stuffed. Context: white, fragile, unchanging when damaged, reaction with guaiac after 5 s negative on both stipe and lamellae surfaces, reaction to FeSO4 and sulfovanillin negative; taste mild; odour inconspicuous. Spore print: not observed.Figure 3Basidiomata of Russula bellissima. (A) FH12-127 (Holotype). (B) FH12-158. Scale bar = 1 cm. Photos by Felix Hampe.Full size imageSpores (Figs. 4, 5) (6.9–)7.3–7.8–8.3(–8.9) × (6.1–)6.8–7.2–7.6(–8.4) µm, subglobose to broadly ellipsoid, Q = 1.01–1.1–1.2(–1.29); ornamentation of moderately distant [(4–)5–6(–7) in a 3 µm diam. circle] amyloid spines or warts, (1.1–)1.2–1.4–1.6(–1.7) µm high, fused or connected by fine line connections into often long crests or wings, [(0–)1–3(–4) fusions and the same number of line connections in a 3 µm diam. circle], crests and wings frequently branched and occasionally form closed loops, isolated elements dispersed, edge of crests and wings irregularly wavy; suprahilar spot moderately large, inamyloid. Basidia: (30.5–)34.5–44.1–53.5(–65.0) × (10.5–)11.5–12.6–14.0(–16.0) µm, broadly clavate or obpyriform, 4-spored; basidiola cylindrical, ellipsoid or broadly clavate, ca. 5–10 µm wide. Hymenial cystidia on lamellae sides: absent. Lamellae edges: covered by densely arranged or fasciculate marginal cells. Marginal cells: (27.0–)38.5–46.4–54.5(–61.0) × (5.0–)5.5–6.7–7.5(–9.0) µm; subulate or narrowly lageniform, apically attenuated and constricted to ca. 1–2 µm, sometimes slightly moniliform or flexuous. Pileipellis: (Fig. 6) orthochromatic in Cresyl Blue, gradually passing to the underlying context, 200–300 µm deep; suprapellis 60–130 µm deep, composed of erect or ascending hyphal terminations forming a dry trichoderm, well delimited from 140 to 210 µm deep subpellis composed of horizontally oriented, strongly gelatinized narrow hyphae. Subpellis not well delimited from the underlying context, elongate hyphae gradually changing to sphaerocytes. Acid- resistant incrustations: absent. Hyphal terminations near the pileus margin: composed of long apically attenuated terminal cell and a chain of 1–4 ovoid to barrel shaped, short unbranched cells with one distinctly longer apical cell; constricted on septa, usually not flexuous, oriented towards the pileus surface, usually thin-walled, sometimes slightly thick-walled (up to 1 µm thick); terminal cells mainly subulate or lageniform, apically attenuated and acute, measuring (19–)27.5–38.3–49.0(–66.5) × (3.3–)4.5–5.8–7.0(–9.0) µm, rarely with a forked apex, mixed with dispersed, cylindrical or ellipsoid, distinctly shorter, obtuse terminal cells measuring (7.5–)11.5–17.8–29.5(–42.5) × (3.0–)4.0–4.5–5.0 µm; subterminal cells measuring (4.5–)5.5–8.3–11.5(–16.0) × 4.5–5.3–6.0(–7.0) µm. Hyphal terminations near the pileus centre: similar in shape and also with a mixture of long acute and short obtuse terminal cells, acute ones measuring (12.0–)22.0–35.2–48.5(–79.0) × (2.5–)3.5–4.9–6.5(–8.0) µm, obtuse ones more frequent, measuring (6.5–)8.5–12.0–15.5(–22.0) × (3.5–)4.0–4.9–6.0(–7.5) µm. Primordial hyphae or pileocystidia: absent. Cystidioid hyphae and oleipherous hyphae not observed.Figure 4Hymenial elements of Russula bellissima (holotype, FH 12-127). (A) Basidia and basidiolae. (B) Marginal cells. (C) Spores as seen in Melzer’s reagent. Scale bar = 10 µm, but only 5 µm for spores.Full size imageFigure 5Scanning electron microscope photo of spore ornamentation. Russula bellissima (holotype, FH 12-127). Scale bar = 2 μm.Full size imageFigure 6Elements of the pileipellis of Russula bellissima (holotype, FH 12-127). (A) Hyphal terminations near the pileus margin. (B) Hyphal terminations near the pileus centre. Scale bar = 10 μm.Full size imageAdditional material studied THAILAND, Chiang Mai Province, Mae On District, about 3 km from Tharnthong lodges, 18° 51′ 55″ N 99° 17′ 23″ E, alt. 725 m, Dipterocarpaceae dominated forest with the presence of some Castanopsis trees, in small groups on loamy soil, 17 July 2012, F. Hampe (GENT FH 12-158, duplicate: MFLU12-0648).Note Russula bellissima is a small species with a bright red pileus and pink colour on the stipe. This colour is distinctive and resembles North American R. mariae, Indian R. intervenosa and Asian R. bella. It is very unlikely that the distribution of any European or North American species is overlapping with the Thai species. However, little is known about the distributional ranges and the ecological niches of other Asian Russula species. Therefore discussing the morphological distinguishing characters between Asian species and R. bellissima is more relevant. Russula bellissima is not closely related to R. bella and it differs from this species by larger spores with a more prominent spore ornamentation, absence of hymenial cystidia on lamellae sides, and subterminally short, ellipsoid cells in the suprapellis arranged in unbranched chains of up to four7. The Thai species resembles and is closely related to the Indian R. intervenosa, but it has a more prominent spore ornamentation, hymenial cystidia (on lamellae sides) are absent, and hyphal terminations in the pileipellis are wider22.
Russula luteonana M. Pobkwamsuk & K. Wisitrassameewong sp. nov.
Mycobank: MB 840550Holotype: THAILAND, Amnat Charoen province, Hua Taphan district, Junction near Watbochaneng , dry dipterocarp forest, alt. 145 m, 15° 41′ 28″ N 104° 31′ 41″ E, 13 July 2016, Thitiya Boonpratuang, Rattaket Choeyklin, Prapapan Sawhasan, Maneerat Pobkwamsuk, Pattrachai Juthamas, Nattawut Wiriyathanawudhiwong, Patcharee Patangwesa (BBH41120).Etymology ‘Luteolus’ = yellow colour, ‘Nanus’ = small. Refer to pileus color and size of the species.Diagnosis Pileus medium-sized, dry, usually yellow, spores with subreticulate amyloid ornamentation and inamyloid suprahilar spot, hymenial cystidia on lamellae sides large, lamellae edges with combination of subulate, clavate and pyriform marginal cells.Pileus (Fig. 7) medium-sized, 28‒53 mm diam., plano-convex with depressed centre, infundibuliform when mature; margin striated and radially cracking in dry condition; cuticle dry, peeling to almost ½ of radius, smooth to minutely wrinkled, dull in dry condition, color very variable, some collections pale cream and with darker pale brownish-yellow centre, other yellow brownish and with darker orange-brown centre, sometimes also bright red-brown and with discolored centre, always with rusty-brown spots especially when near the centre. Lamellae: 3‒5 mm deep, moderately distant, intervenose, forking near the stipe, white to cream, edges even, concolorous. Stipe: 26‒40 × 6‒9 mm, cylindrical or narrowed at the base, surface dry, longitudinally wrinkled, white, turning brown when bruised. Context: 2‒4 mm in at the half pileus radius, soft, solid, becoming partially hollow when mature, white, unchanging when cut. Taste mild; odour rather strong, fishy. Spore print: not observed.Figure 7Basidiomata of Russula luteonana. (A) BBH41120 (Holotype). (B) BBH41121. (C) BBH41122. (D) BBH42510. Scale bar = 1 cm. Photos by Thitiya Boonpratuang.Full size imageSpores (Figs. 8, 9) (7.4‒)8.1‒8.6‒9(‒10.1) × (6.1‒)7.4‒7.5‒7.9(‒9.1) μm, subglobose to broadly ellipsoid, Q = (1.03‒)1.09‒1.15‒1.20(‒1.30), ornamentation of moderately distant, obtuse, (0.7‒)1.1‒1.3‒1.5(‒1.9) μm high spines, connected by abundant line connections [(0‒)3‒6(‒8) in in a 3 µm diam. circle], branched, forming an incomplete reticulum, crest irregularly wavy and occasionally fused [(0‒)1‒2(‒5) fusions in the circle], isolated elements rare; suprahilar spot inamyloid. Basidia: (29‒)34.5‒39.1‒44(‒51.5) × (10‒)12‒13.2‒14.5(‒16.5) μm, clavate, 4-spored, rarely 2-spored, basidiola subcylindrical to subclavate, (25.5‒)30‒35.4‒41(‒47) × (9‒)11‒12.2‒14 (‒16) μm. Hymenial cystidia on lamellae sides: usually protruding over other elements of hymenium, widely dispersed ( More

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Phyla Bdellovibrionota, Fusobacteriota, and Myxococcota were present in the green microbial mat but in negligible quantities in the brown mat. The unique phyla detected in the brown mat, but not in the green microbial mat, included Caldatribacteriota, Thermodesulfobacteriota, Dictyoglomota, Elusimicrobiota, Thermotogota, Candidatus Calescamantes, Fervidibacteria, Hydrothermae, GAL15 and TA06. The Candidatus Caldatribacterium (phyla Caldatribacteriota), earlier named OP9 was also detected in this work. Using single-cell and metagenome sequencing, data elucidated that Ca. Caldatribacterium conducts anaerobic sugar fermentation and exhibited diverse glycosyl hydrolases, including endoglucanase37.Cyanobacteria and Chloroflexota were the main identified phyla in the green microbial mat. Because the hot spring is almost stagnant, undisturbed, and the water surface temperature ( More

Tropical forest restoration areaTo determine the geographic distribution of land available for tropical forest restoration, we used a widely applied global forest restoration map2. This dataset limits potential restoration area to regions that are biogeophysically suitable for forest, and excludes croplands. To define the tropics, we masked the potential restoration map with the following three ecoregions from the Ecoregions2017 vegetation map34: ‘Tropical and Subtropical Moist Broadleaf Forests’, ‘Tropical and Subtropical Dry Broadleaf Forests’, and ‘Tropical and Subtropical Coniferous Forests’. The resulting restoration mask includes all tropical and subtropical forest ecoregions with some that are outside the tropical latitudes, but excludes wetlands and high mountain areas (Extended Data Fig. 4). The restoration mask was converted from a presence–absence raster at its native ~350 m resolution to a 0.5° geographical grid by aggregating to the fraction of each 0.5° grid cell available for restoration. Any uncertainties in the allocation of restorable area, distinguishing crop and pasture, and forest to non-forest classification from the original forest restoration map were also implicitly included in our restoration extent. While the resulting restoration area is relatively small, its spatial distribution is representative for most of the humid tropics.To prioritize for carbon uptake capacity, we selected all grid cells with restoration area greater than 1 ha and ranked these by carbon storage density (above ground and below ground; g m−2) at 2100 under the default scenario. We then selected the top n grid cells with greatest carbon density until cumulatively 64 Mha of restored area was reached. Similarly, for cost we calculated the restoration cost for each grid cell following ref. 27 and sorted the grid cells by their cost, beginning with the lowest value, until 64 Mha were reached. To consider the combined impact of carbon uptake and restoration costs, we divided our restoration cost layer by the total carbon uptake per grid cell from restoration and ranked the cost per carbon uptake from cheapest to most expensive, selecting the n grid cells with the lowest values until 64 Mha were reached. We then used the selected grid cells to mask carbon uptake under the various climate change and CO2 fertilization scenarios. To factor in climate change in the prioritization process, we used the same restoration cost layer but used the carbon density and total carbon uptake layers with climate change impacts in CO22014 for the year 2100.Vegetation modelWe used the LPJ-LMfire DGVM19, a version of the Lund-Potsdam-Jena DGVM (LPJ)35. LPJ-LMfire is driven by gridded fields of climate, soil texture and topography at 0.5° resolution, and with a time series of atmospheric CO2 concentrations (see Supplementary Information). To simulate land use, LPJ-LMfire separates grid cells into fractional tiles of ‘unmanaged’ land that has never been under land use, ‘managed’ land, and areas ‘recovering’ from land use36. Restoration removes land from the ‘managed’ tile and transfers it to the ‘recovering’ tile; land is never reallocated to the ‘unmanaged’ tile. The tiles are treated differently with respect to wildfire: on the ‘unmanaged’ and ‘recovering’ tiles, lightning-ignited wildfires are not suppressed, while fire is excluded from ‘managed’ tiles. For our analysis of total carbon (above and below ground), we only used the ‘recovering’ tile.Climate dataClimate forcing used to drive LPJ-LMfire comes from the output of 13 GCMs in simulations produced for the CMIP6 Supplementary Table 2 (refs. 37,38). For each GCM, we obtained simulations for the historical period (1850–2014) and four future SSPs (SSP1-26, SSP2-45, SSP3-70 and SSP5-85 covering 2015–2100). We used only GCMs that archived all seven climate variables needed to run LPJ-LMfire: 2 m temperature (tas, K), precipitation (pr, kg m−2 s−1), convective precipitation (prc, kg m−2 s−1), cloud cover (clt, %), minimum and maximum daily temperature (tmin, tmax, K), and 10 m surface wind speed (sfcWind, m s−1) (Supplementary Fig. 2). For each model, we concatenated the historical simulation with a future scenario, calculated anomalies with respect to 1971–1990 and added those to observed 30 year climatologies to create bias-corrected monthly climate time series covering 1850–2100 (see Supplementary Information). Where multiple ensemble members were available from a GCM, we chose the first simulation.Simulation protocolWe drove LPJ-LMfire with the GCM simulations described in the previous section, and the same atmospheric CO2 concentrations and land use boundary conditions as those used in the CMIP6 simulations. All forcings cover the historical period (1850–2014) and the individual future SSPs (2015–2100). Each LPJ-LMfire simulation was initialized for 1,020 years with 1850 atmospheric CO2 and land use, and the 1850s climatology of each CMIP6 GCM. This was followed by simulations with transient climate from 1850 to 2100 for each CMIP6 GCM under each of the four SSPs. For each the 13 CMIP6 GCMs running each of the SSP scenarios, we conducted two CO2 experiments (CO22014 and CO2free) and two fire experiments. In total, we ran 221 vegetation model simulations covering the range of future climate, CO2 and fire scenarios.Atmospheric CO2 in these simulations either followed the CMIP6 historical and SSP trajectory for the entire 1850–2100 run (CO2free), or followed the historical CMIP6 trajectory until 2014, and was then fixed at 2014 concentrations for the remainder of the simulation (CO22014). This allowed us to test the vegetation response to future climate change in the absence of additional CO2 fertilization of photosynthesis. Our simulations ended with the standard SSP projections in 2100, 80 years after restoration begins. We therefore could not assess the fate of restored carbon beyond that point. On the basis of the trends in the multi-model mean carbon uptake rates, we estimated that only under severe climate change will carbon storage be reduced shortly after 2100 in CO22014.In control simulations, land use followed the historical CMIP6 trajectory until 2014, after which it was fixed under 2014 conditions until 2100. Land use after 2014 was fixed at 2014 levels because it is the last year with common land use between all scenarios, which allowed us to identify future climate change impacts on restoration permanence and avoid influences from land abandonment and expansion prescribed in the different SSP scenarios.In the restoration experiments, land use also followed the historical CMIP6 trajectory until 2014, but then diverged: cropland extent remained at 2014 levels until 2100, while pasture (or non-cropland land use) remained constant from 2014 to 2020 and was then linearly reduced by the restoration area from 2020 to 2030. From 2030, land use remained constant at that lower level until 2100. The amount of restoration in a grid cell was limited by the pasture area, that is, once all of the available pasture area had been restored, no additional restoration took place. Because it is highly unlikely to be practical to restore the entire target area of tropical forest at once, we linearly increased the restoration area from 2020 to 2030, which caused an expansion-driven increase in carbon uptake over the 11 year period (Extended Data Fig. 1). This means that two factors controlled carbon uptake over time in our experimental design: first the expansion of the restoration area, accounting for approximately 19.7 Pg C, and second the long-term effect of carbon accumulation (Extended Data Fig. 5).Primary climate change impacts, such as drought and heat stress that reduce carbon uptake, were implicitly included in the climate forcing data, while secondary climate change impacts from wildfire were simulated by LPJ-LMfire on the basis of climate. To quantify the contribution of wildfire on the carbon storage from restoration, we repeated the simulations described above with fires turned off in LPJ-LMfire.Restoration opportunity indexWe created a restoration opportunity index to evaluate the suitability of locations for restoration on the basis of the ability for restoration to result in net carbon uptake over 2020–2100 and to store this carbon without episodes of major loss. For each of the 13 realizations of the four SSPs in the CO22014 experiment, we identified all restoration grid cells (1) that had a net carbon uptake by 2100 relative to 2030, and (2) where temporal reductions in total carbon storage over 2030–2100 were More

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