More stories

  • in

    Obscured fishing activity

    Welch and colleagues analysed 3.7 billion AIS messages recorded between 2017 and 2019 in the global Fishing Watch AIS dataset, identifying more than 55,000 suspected intentional disabling events in waters more than 50 nautical miles from shore, amounting to 6% ( >4.9 million hours) of obscured vessel activity. Hotspots of disabling activity were located near several regions of IUU concern and transshipment hotspots, including in the exclusive economic zones of Argentina and West African nations and in the Northwest Pacific. Using individual boosted regression tree models for the four dominant gear types (squid jiggers, trawlers, tuna purse seines and drifting longlines) and a full model that included all suspected disabling events (that is, the four gear types listed above and additional gears such as gillnet and troll), Welch and colleagues found that loitering by transshipment vessels (a proxy for potential transshipment events) was the most important driver in the full model and squid jigger model and more than half of the disabling events by squid jiggers were close enough to undertake transshipment to refrigerated cargo vessels. More

  • in

    Diversity of Trichoderma species associated with soil in the Zoige alpine wetland of Southwest China

    Trichoderma species collectionEighty strains were obtained from 100 soil samples collected from Zoige alpine wetland ecological regions in China. Details of the strains isolated from soil samples are given in Table 1. All strains were subsequently used for morphological identification, while fifty-seven were used for phylogenetic analysis.Table 1 Details of 80 Trichoderma isolates from the Zoige alpine wetland in this study.Full size tablePhylogenetic analysisThe ITS region used preliminarily as a species identification criterion was applied to TrichOKey at www.ISTH.info70. However, the ITS region has a low number of variable sites and long insertions in certain species; thus, it is unsuitable for a phylogenetic reconstruction of this group41. Our study successfully amplified most fragments of the genes tef1, rpb2, and acl1. We also designed a pair of new primers based on the full-length tef1 gene, 5′-GAGAAGTTCGAGAAGGTGAGC-3′ and 5′-ATGTCACGGACGGCGAAAC-3′, with which a 1.4-kb fragment was amplified for most isolates.All samples analyzed in our study were divided into 4 primary clades based on the gpd gene region, including 49 strains from the T. harzianum complex, 3 T. rossicum strains, 1 T. polysporum strain and one unknown species (4 Trichoderma sp. strains) (Fig. 1). Maximum parsimony analysis was conducted among 101 strains, with Protocrea farinosa (CPK 2472) and P. pallida (CBS 299.78) used as outgroup (Table 2). The dataset for the rpb2, tef1 and acl1 genes contained 3403 characteristics, among which 1152 were parsimony-informative, 988 were variable and parsimony-uninformative, and 1263 were constant. The most parsimonious trees are shown in Fig. 2 (tree length = 5054, consistency index = 0.6005, homoplasy index = 0.3995, retention index = 0.8105, rescaled consistency index = 0.4867).Figure 1Neighbor-joining tree based on partial gpd gene sequences from 57 Trichoderma isolates. Parsimony bootstrap values of more than 50% are shown at nodes.Full size imageTable 2 Trichoderma strain included in the multi-gene sequence analysis, with details of clade, strain number, location, and GenBank accessions of the sequences generated.Full size tableFigure 2Maximum parsimony tree of Trichoderma species inferred from the combined rpb2, tef1 and acl1 partial sequences. Maximum parsimony bootstrap values above 50% are shown at nodes. The tree was rooted with Protocrea farinose and P. pallida Isolates from this study are shown in red (new species in bold).Full size imageThe phylogram showed that 57 stains belonged to the following four clades: Harzianum, Polysporum, Stromaticum, and Longibrachiatum. The strains of the first three clades with neighboring named species were well supported by bootstrap values greater than 90%. The Harzianum clade contained T. alni, T. atrobrunneum, T. harzianum and T. pyramidale of the Trichoderma species complex. The Polysporum clade contained only T. polysporum, and the Stromaticum clade contained T. rossicum. The Longibrachiatum clade contained four strains of Trichoderma sp., T25, T43, T44 and T48, which were separated from any other known taxa of this clade showed a low bootstrap value (MPBP = 62%) with T. citrinoviride and T. saturnisporum. We thus regarded it as a new species and named it Trichoderma zoigense, as described in the next section.Growth ratesAs shown in Fig. 3, the genus Trichoderma from Zoige alpine wetland ecological regions was able to grow in a range from 15 to 35 °C, and the suitable growth temperature for most species ranged from 20 to 30 °C. All seven species identified had normal viability at relatively low temperature (15 °C), and they rarely grew well over 35 °C except for T. zoigense. For T. atrobrunneum, T. harzianum and T. pyramidale, the optimum growth temperature on CMD was 25 to 30 °C. T. alni and T. rossicum preferred a cool growth environment, with an optimum temperature of 25 °C, whereas T. zoigense was more partial to a hot environment, with an optimum temperature of 30 °C, and it even grew well up to 35 °C. T. polysporum was the only slow-growing species that grew with less than 6.0 mm/day between 15 and 30 °C and did not survive at 35 °C. The above results showed that all species had different growth rates but were not completely differentiated from each other on CMD. These species were roughly divided into four groups based on their optimum growth temperature.Figure 3Growth rates of 7 species of Trichoderma on CMD given as mm per day at five temperatures. The values were the means of 3–5 experiments, with 1–3 representative isolates per species.Full size imageRelationship with ecological factorsOur results revealed a substantial disparity in the number and distribution of Trichoderma species among Zoige alpine wetland ecological regions (Tables 3, 4). Table 3 showed that T. harzianum was found in all four soil types, but most isolates of this species were obtained from peat soil. T. rossicum, T. alni and T. zoigense were also present in meadow soil and subalpine meadow soil, whereas T. atrobrunneum was found in aeolian sandy soil and peat soil. T. polysporum was found only in peat soil.Table 3 Isolation frequency of Trichoderma species in different soil types (%).Full size tableTable 4 Isolation frequency of Trichoderma species in different soil layers (%) species.Full size tableIn regard to the different soil layers shown in Table 4, T. harzianum was widely distributed in the five soil layers at depths of 0–100 cm. T. rossicum, T. alni and T. zoigense were isolated mainly from the soil layers at depths of 0–50 cm. Both T. atrobrunneum and T. pyramidale were isolated from depths of 0–10 cm, and T. polysporum was found only in the soil layers at depths of 50–100 cm.Regarding isolation frequency, T. harzianum was the most common of the seven species with a 23% isolation frequency, and it was therefore the dominant species in the zone, while the rare species T. polysporum and T. pyramidale had the lowest isolation frequencies at 1%.TaxonomyNew speciesTrichoderma zoigense G.S. Gong & G.T. Tang, sp. nov. (Fig. 4).Figure 4Cultures and asexual morph of Trichoderma zoigense. (a–d). Cultures at 20 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 4 days; and (d) on SNA, 7 days]. (e) Conidiation tuft (CMD, 4 days). (f–k) Conidiophores and phialides (CMD, 5–7 days). (l) Chlamydospores (PDA, 8 days). (m) Conidia (CMD, 5 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageMycoBank: MB 82114.Typification: CHINA. SICHUAN PROVINCE: Zoige Alpine Wetland, on soil, 29 June 2013, G.S. Gong T44 (holotype CGMCC3.20145). GenBank: ITS = KX632531; TEF = KX632588; RPB2 = KX632645; ACL1 = KX632702; GPD = KX632759.Etymology: zoigense (Latin), the specific epithet about the place where the type was found.Description: Cultures and anamorph: optimal growth at 25 °C on all four media. On CMD after 72 h, growth is 25–28 mm at 20 °C and 28–31 mm at 25 °C. Colony is dense and has a wavy to crenate margin. Surface becomes distinctly zonate and white to grayish-green but celadon to atrovirens later, and it is granular in the center and distinctly radially downy outside and shows whitish surface hyphae and reverse-diffusing croci to pale brown pigment (Fig. 4a). Aerial hyphae are numerous to punctate and long, forming radial strands, with white mycelial patches appearing in aged cultures (Fig. 4e). Autolytic excretions are rare, with no coilings observed. Conidiation was noted after 3–4 d at 25 °C, a yellow or greenish color appears after 7 days, conidiation is effuse, and in intense tufts, erect conidiophores occur around the plug and on aerial hyphae. They are mainly concentrated along the colony center, show a white color that turns green, and then finally degenerate, with conidia often adhering in chains. Conidiophores are short and simple with asymmetric branches. Branches produce phialides directly. Phialides are generally solitary along main axes and side branches and sometimes paired in the terminal position of the main axes, sometimes in whorls of 2–3. Phialides are 4.5–10.5 × 2–5 μm ((overline{x }) = 7.5 ± 1.5 × 3 ± 0.5, n = 50) and 1.5–2.5 μm ((overline{x }) = 2 ± 0.2) wide at the base, lageniform or ampulliform, mostly uncinate or slightly curved, less straight, and often distinctly widened in the middle (Fig. 4f–k). Conidia are 3–4.5 × 2.3–4 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.3, n = 50) and initially hyaline, and they turn green and are oblong or ellipsoidal, almost with constricted sides, and smooth, eguttulate or with minute guttules, with indistinct scars (Fig. 4m).On PDA, after 72 h, growth is 35–41 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5 days at 25 °C. Colonies are dense with wavy to crenate margins; and mycelia are conspicuously differentiated in width of the primary and secondary hyphae. Surface becomes distinctly zonate, yellowish-green to prasinous in color and celadon to atrovirens later, and it is farinose to granular in the center, distinctly radially downy outside, with whitish of surface hyphae and reverse-diffusing brilliant yellow to fruit-green pigment (Fig. 4c). Aerial hyphae are numerous, long and ascend several millimeters, forming radial strands, with white mycelial patches appearing in aged cultures. Autolytic excretions are rare; and no coilings are observed. Odor is indistinct or fragrant. Chlamydospores examined after 7 days at 4.5–9 × 4.5–7.5 μm ((overline{x }) = 6 ± 1.1 × 6 ± 0.7, n = 50), and they are terminal, intercalary, globose or ellipsoidal, and smooth (Fig. 4l). Conidiation is noted after 3–4 days and yellow or greenish after 7 days. Conidiophores are short and simple with asymmetric branches; conidia are greenish, ellipsoidal, and smooth.On SNA, after 72 h, growth is 13–15 mm at 20 °C and, 16–21 mm at 25 °C; and mycelium covers the plate after 12–13 days at 25 °C. Colony is similar to that on CMD, with a little wave margin, although mycelia are looser and slower on the agar surface. Aerial hyphae are relatively inconspicuous and long along the colony margin. Autolytic activity and coiling are absent or inconspicuous. No diffusing pigment or distinct odor are produced (Fig. 4d). Conidiation was noted after 3–4 days at 25 °C, and many amorphous, loose white or aqua cottony tufts occur, mostly median from the plug outwards, and they are confluent to masses up and white but then turn green. After 4–5 days, conidiation becomes dense within the tufts, which are loose at their white margins with long, straight, or slightly sinuous sterile ends in the periphery. Tufts consisting of a loose reticulum with branches often at right angles, give rise to several main axes. Main axes are regular and tree-like, with few or many paired or unpaired side branches. Branches are flexuous, and phialides are solitary along the main axes and side branches, and they are sometimes paired in the terminal position of the main axes, sometimes in whorls of 2–3 that are often cruciform or in pseudo-whorls up to 4. Phialides and conidia are similar to that on CMD.New records for ChinaTrichoderma atrobrunneum F. B. Rocha et al., Mycologia 107: 571, 2015 (Fig. 5).Figure 5Cultures and asexual morph of Trichoderma atrobrunneum. (a–d) Cultures at 25 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 15 days; and (d) on SNA, 7 days]. (e) Conidiation tuft (SNA, 7 days). (f–i,k,l) Conidiophores and phialides (CMD, 5–7 days). (j) Conidia (CMD, 6 days). (m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageSpecimen examined: CHINA. SICHUAN PROVINCE: Zoige Alpine Wetland, on soil, 29 June 2013, G.S. Gong T42 (holotype CGMCC.20167). GenBank: ITS = KX632514; TEF = KX632571; RPB2 = KX632628; ACL1 = KX632685; GPD = KX632742.Description: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, after 72 h, growth is 35–37 mm at 20 °C and 46–53 mm at 25 °C; mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow, sinuous and often form strands on the margin (Fig. 5a). Aerial hyphae are slight, forming a thin white to green downy fluffy or floccose mat. The light brown or brown pigment is observed, with no distinct odor noted. Conidiophores are pyramidal, often with opposing and somewhat widely spaced branches, with the main axis and each branch terminating in a cruciate, sometimes verticillate, whorl of up to four phialides. Phialides are ampulliform to lageniform and 4.9–7.6 × 2.2–3.0 μm ((overline{x }) = 6 ± 0.7 × 2.5 ± 0.2, n = 50) and 1.5–2.5 μm ((overline{x }) = 1.5 ± 0.3) wide at the base (Fig. 5f–i,k,l). Conidia are 2.5–4 × 2.5–3.5 μm ((overline{x }) = 3 ± 0.3 × 3 ± 0.2, n = 50), yellow to green, smooth, and circular to ellipsoidal (Fig. 5j).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 5c). Margin is thick and defined. Aerial hyphae are abundant and form a thick green downy mat. Conidiation forms abundantly within 4 days in broad concentric rings. Chlamydospores examined after 7 days are 5–9 × 5.5–8.5 μm ((overline{x }) = 6.5 ± 0.9 × 6.5 ± 0.9, n = 30), globose when terminal, smooth, and intercalary (Fig. 5m).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and yellow to green; hyphae are wide and sinuous, with indistinct strands on the margin (Fig. 5d). Margin is thin and ill-defined. Aerial hyphae are slight, forming a thin green downy fluff appearing in the colony (Fig. 5e). Diffusing pigment was observed in a ring, and no distinct odor was noted. Conidiation is similar to CMD.Accepted species previously reported in ChinaTrichoderma alni Jaklitsch, Mycologia 100: 799. 2008 (Fig. 6).Figure 6Cultures and asexual morph of Trichoderma alni. (a–d). Cultures after 7 days at 25 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. € Coilings of aerial hyphae (PDA, 6 days). (f–j,l). Conidiophores and phialides (CMD, 5–7 days). (k) Conidiation tuft (PDA, 7 days). (m) Conidia (CMD, 6 days). (n,o) Chlamydospores (PDA, 7 days). Scale bars: (e–j,l–o) = 10 μm; (k) = 2 mm.Full size imageDescription: Cultures and anamorph: Optimum growth at 25 °C on all media; no growth at 35 °C. On CMD, after 72 h, growth of 34–36 mm at 20 °C and 50–51 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow and sinuous and often form strands on the margin (Fig. 6a). Aerial hyphae are slight and form a thin white to green downy, fluffy or floccose mat. No diffusing pigment or distinct odor is noted. Conidiophores are hyaline and thick, with side branches on several levels at the base of the elongations that are mostly paired and in right angles with phialides in whorls of 3–5. Phialides are 5.5–11.5 × 2–3.5 μm ((overline{x }) = 8 ± 1.4 × 2.5 ± 0.4, n = 50) and 1.5–2.5 μm ((overline{x }) = 2 ± 0.4) wide at the base, often short and wide, and ampulliform (Fig. 6f–j,l). Conidia are 3–4 × 2.5–3.5 μm ((overline{x }) = 3.5 ± 0.2 × 3 ± 0.2, n = 50), dark green, smooth, and ellipsoidal (Fig. 6m).On PDA, after 72 h, growth is 33–35 mm at 20 °C and 41–43 mm at 25 °C; and mycelium covers the plate after 6–7 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 6c). Margin is thin and ill defined. Aerial hyphae are slight, coiled (Fig. 6e), forming a thin white to green downy, fluffy or floccose mat (Fig. 6k). Chlamydospores examined after 7 days are 6–9.5 × 5–8 μm ((overline{x }) = 7.5 ± 0.9 × 7 ± 0.9, n = 30), globose to oval when terminal, and smooth, and few are intercalary (Fig. 6n,o).On SNA, after 72 h, growth is 18–19 mm at 20 °C and 28–32 mm at 25 °C; and mycelium covers the plate after 6–7 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and yellow to green; hyphae are wide and sinuous and show indistinct strands on the margin (Fig. 6d). Margin is thin and ill-defined. Aerial hyphae are slight and form a thin white downy, fluffy, or floccose mat appearing in distal parts of the colony. No diffusing pigment or distinct odor was noted. Conidiation is similar to CMD.Trichoderma harzianum Rifai, Mycol. Pap. 116: 38, 1969 (Fig. 7).Figure 7Cultures and asexual morph of Trichoderma harzianum. (a–d) Cultures after 7 days at 20 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. (e) Conidiation tuft (CMD, 7 days). (f–j) Conidiophores and phialides (CMD, 5–7 days). (k) Conidia (CMD, 5 days). (l,m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–m) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, after 72 h, growth is 34–38 mm at 20 °C and 46–53 mm at 25 °C; mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are loose and thin; hyphae are narrow, sinuous, and often form strands on the margin (Fig. 7a). Aerial hyphae are abundant and radiating and form thick green downy, fluffy, or floccose mats (Fig. 7e). No diffusing pigment, but fragrant odor noted. Conidiophores are pyramidal with opposing branches, with each branch terminating in a cruciate whorl of up to four or five phialides. Phialides are frequently solitary or in a whorl of three or four. Phialides are ampulliform to lageniform and often constricted below the tip to form a narrow neck of 4.5–8 × 2–3.5 μm ((overline{x }) = 6 ± 0.8 × 2.5 ± 0.3, n = 50) and 1–2.5 μm ((overline{x }) = 2 ± 0.3) wide at the base (Fig. 7f–j). Conidia are subglobose to ovoid, 3–4.5 × 2.5–3.3 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.2, n = 50), laurel-green to bright green, smooth, and ellipsoidal (Fig. 7k).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide and sinuous and often form strands on the margin (Fig. 7c). Margin is thick and ill defined. Aerial hyphae are abundant and radiating and form thick green downy, fluffy or floccose mats. Chlamydospores examined after 7 days are 5.5–9 × 5.5–9.0 μm ((overline{mathrm{x} }) = 7 ± 0.8 × 7 ± 0.8, n = 30), globose to oval when terminal and smooth, showing an almost unobserved intercalary (Fig. 7l,m).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelia are thin and green; hyphae are narrow and sinuous and show indistinct strands on the margin (Fig. 7d). Margin is thin and ill defined. Aerial hyphae are slight and form a thick downy, fluffy, or floccose mat appearing in the colony. No diffusing pigment or distinct fragrant odor was noted. Conidiation was similar to CMD.Trichoderma polysporum Rifai, Mycol. Pap. 116: 18, 1969 (Fig. 8).Figure 8Cultures and asexual morph of Trichoderma polysporum. (a–d) Cultures at 20 °C [(a) on CMD, 7 days; (b) on MEA, 15 days; (c) on PDA, 15 days; and (d) on SNA, 15 days]. (i) Conidiation tuft (PDA, 15 days). (e–h,j) Conidiophores and phialides (CMD, 5–7 days). (k) Chlamydospores (CMD, 7 days). (l) Conidia (PDA, 6 days). Scale bars: (i) = 2 mm; (e–h,j) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 20 °C on all media, no growth at 35 °C. On CMD, after 72 h, growth is 14–16 mm at 20 °C and 9–12 mm at 25 °C; and mycelium covers the plate after 9–10 days at 20 °C. A colony is hyaline, thin and loose, with little mycelium on the agar surface, and it is indistinctly zonate but becomes zonate by conidiation in white tufts after 4–5 d and grass green to green after 6 days (Fig. 8a). Aerial hyphae are long and dense and forming little greenish aggregates that are granular to pulvinate. No pigment or odor. Conidiation noted after 4–5 days, and it is white to greenish, with sterile smooth to rough helical elongations in the distal zones from pustules. Conidiophores are hyaline and thick with side branches on several levels at the base of the elongations that are mostly paired and at right angles with phialides in whorls of 2–5. Phialides are 5–10.5 × 2.5–4 μm ((overline{x }) = 7 ± 1.9 × 3.5 ± 0.4, n = 50) and 2–4 μm ((overline{x }) = 3 ± 0.5) wide at the base, often short and wide and ampulliform (Fig. 8e–h,j). Conidia are 2.5–4 × 2–3 μm ((overline{x }) = 3.5 ± 0.4 × 2.5 ± 0.2, n = 50), hyaline, smooth, and ellipsoidal (Fig. 10l).On PDA, after 72 h, growth is 24–26 mm at 20 °C and 13–16 mm at 25 °C; and mycelium covers the plate after 8–9 days at 20 °C. A colony is densest, distinctly zonate, and grass green to spearmint green; mycelia are conspicuously dense; and surface hyphae form radial strands (Fig. 8c). Aerial hyphae are long and dense and form greenish aggregates that are granular to pulvinate (Fig. 8i). No diffusing pigment and odor. Chlamydospores examined after 7 days are 5.5–9 × 5–7.5 μm ((overline{x }) = 7 ± 0.9 × 6 ± 0.6, n = 30), globose to oval when terminal, and smooth, with an almost unobserved intercalary (Fig. 8k).On SNA, growth is approximately 7 mm/day at 20 °C and 5 mm/day at 25 °C; and mycelium covers the plate after 10 days at 20 °C. A colony is hyaline, thin, and loose, with little mycelium on the agar surface, not or indistinctly zonate, but becomes zonate by conidiation in white tufts after 4–5 days; and the margin is downy by long aerial hyphae, which degenerating/dissolving soon (Fig. 8d).Trichoderma pyramidale W. Jaklitsch & P. Chaverri, Mycologia 107: 581, 2015 (Fig. 9).Figure 9Cultures and asexual morph of Trichoderma pyramidale. (a–d) Cultures at 25 °C [(a) on CMD, 7 days; (b) on MEA, 4 days; (c) on PDA, 4 days; and (d) on SNA, 4 days]. (e) Conidiation tuft (PDA, 7 days). (f–j) Conidiophores and phialides (CMD, 5–7 days). (k) Conidia (CMD, 6 days). (l) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–l) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media, with little growth at 35 °C. On CMD, after 72 h, growth is 29–32 mm at 20 °C and 48–53 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show distinct zonation. Mycelium is loose and thin; hyphae are narrow, sinuous, and often form strands on the margin (Fig. 9a). Aerial hyphae are slight, forming a thin white to green downy, fluffy or floccose mat. Brown pigment is shown, but no distinct odor noted. Conidiophores are hyaline and thick with side branches on several levels at the base of the elongations that are mostly paired and at right angles with phialides in whorls of 3–5. Phialides are 5–9.5 × 2.5–3 μm ((overline{x }) = 7 ± 1.1 × 3 ± 0.3, n = 50) and 1–2.5 μm ((overline{x }) = 1.5 ± 0.3) wide at the base and often short, wide, and ampulliform (Fig. 9f–j). Conidia are 2.5–4 × 2.5–3.5 μm ((overline{x }) = 3.5 ± 0.3 × 3 ± 0.2, n = 50), green, smooth, and ellipsoidal (Fig. 9k).On PDA, after 72 h, growth is 41–43 mm at 20 °C and 50–55 mm at 25 °C; and mycelium covers the plate after 5–6 days at 25 °C. Colonies show indistinct zonation. Mycelia are dense, opaque, and thick; hyphae are wide, sinuous and often form strands on the margin (Fig. 9c). Margin is thin and ill defined. Aerial hyphae are slight and form a thin white to green downy, fluffy or floccose mat (Fig. 9e). Chlamydospores examined after 7 days are 5.5–10 × 5.5–10 μm ((overline{x }) = 7 ± 0.9 × 7 ± 0.9, n = 30), globose to oval when terminal or intercalary, and smooth (Fig. 9l).On SNA, after 72 h, growth is 33–35 mm at 20 °C and 38–40 mm at 25 °C; and mycelium covers the plate after 7–8 days at 25 °C. Colonies show distinct zonation. Mycelium is thin, yellow to green; hyphae are wide, sinuous, with indistinct strands on the margin (Fig. 9d). Margin is thin and ill defined. Aerial hyphae are slight and form a thin white downy, fluffy or floccose mat in distal parts of the colony. No diffusing pigment or distinct odor noted. Conidiation similar to CMD.Trichoderma rossicum Bissett et al., Canad. J. Bot. 81: 578, 2003 (Fig. 10).Figure 10Cultures and asexual morph of Trichoderma rossicum. (a–d) Cultures after 7 days at 25 °C [(a) on CMD; (b) on MEA; (c) on PDA; and (d) on SNA]. € Conidiation tuft (PDA, 7 days). (f–h,j,k) Conidiophores and phialides (CMD, 5–7 days). (i) Elongations (CMD, 6 days). (l,n) Conidia (CMD, 6 days). (m) Chlamydospores (PDA, 7 days). Scale bars: (e) = 2 mm; (f–n) = 10 μm.Full size imageDescription: Cultures and anamorph: optimal growth at 25 °C on all media. On CMD, growth of 10–11 mm/day at 20 °C and 15–17 mm/day at 25 °C; and mycelium covers the plate after 6–7 days at 20 °C. Colony is dense with a wavy margin, and the surface becomes distinctly zonate (Fig. 10a). Aerial hyphae are numerous, long, elongate, and villiform in the plate (Fig. 10i). No diffusing pigment or odor. Autolytic activity is variable, and coilings are scarce or inconspicuous. Conidiation noted after 3–4 days at 20 °C. Conidiation is effuse and in intense tufts that are hemispherical or irregular, and they show wide wheel grain banding that is gray green to deep green. Conidiophores radiate from the reticulum and are broad, straight, sinuous or helically twisted, show distally slightly pointed elongations, taper from the main axes to top branches, and present primary branches arranged in pairs or in whorls of 2–3, with secondary branches to solitary. Phialides are 4.5–14 × 2.5–4 μm ((overline{x }) = 7 ± 1.5 × 3.5 ± 0.3, n = 50) and 2–3.5 μm ((overline{x }) = 3 ± 0.4) wide at the base, ampulliform, and in whorls of 3–6 (Fig. 10f–h,j,k). Conidia are 3.5–5.5 × 2.5–4 μm ((overline{x }) = 4.5 ± 0.5 × 3 ± 0.2, n = 50), short cylindrical, and a gray color when single and pea green to yellow green in a group (Fig. 10l,n).On PDA, growth is 12–15 mm/day at 20 °C, 12–16 mm/day at 25 °C; and mycelium covers the plate after 4–5 days at 25 °C. Colony is denser with a wavy margin than that on CMD, and the surface is distinctly zonate (Fig. 10c). Aerial hyphae are numerous, long, and villiform to pulvinate in the plate. No diffusing pigment and odor (Fig. 10e). Autolytic activity is variable, coilings are scarce or inconspicuous. Chlamydospores examined after 7 days are 6.5–9.5 × 6–9 μm ((overline{x }) = 7 ± 1.0 × 7 ± 0.9, n = 30), terminal and intercalary, globose or ellipsoidal, and smooth (Fig. 10m).On SNA, growth is 8–13 mm/day at 20 °C and 8–12 mm/day at 25 °C; and mycelium covers the plate after 6–7 day at 25 °C. Colony is hyaline, thin and dense; and mycelium degenerate rapidly (Fig. 10d). Aerial hyphae are inconspicuous, autolytic activity is scant, and coilings are distinct. Conidiation noted after approximately 4 days and starts in white fluffy tufts spreading from the center to form concentric zones, and they compact to pustules with a white to greenish color. More

  • in

    Global habitat suitability modeling reveals insufficient habitat protection for mangrove crabs

    Valiela, I., Bowen, J. L. & York, J. K. Mangrove Forests: One of the World’s Threatened Major Tropical Environments: At least 35% of the area of mangrove forests has been lost in the past two decades, losses that exceed those for tropical rain forests and coral reefs, two other well-known threatened environments. Bioscience 51, 807–815. https://doi.org/10.1641/0006-3568(2001)051[0807:MFOOTW]2.0.CO;2 (2001).Article 

    Google Scholar 
    Kuenzer, C., Bluemel, A., Gebhardt, S., Quoc, T. V. & Dech, S. Remote sensing of mangrove ecosystems: A review. Remote Sens. 3, 1. https://doi.org/10.3390/rs3050878 (2011).Article 

    Google Scholar 
    Turschwell, M. P. et al. Multi-scale estimation of the effects of pressures and drivers on mangrove forest loss globally. Biol. Cons. 247, 108637. https://doi.org/10.1016/j.biocon.2020.108637 (2020).Article 

    Google Scholar 
    Millennium Ecosystem Assessment. Ecosystems and Human Well-being: Synthesis. (2005).Nagelkerken, I. et al. The habitat function of mangroves for terrestrial and marine fauna: A review. Aquat. Bot. 89, 155–185. https://doi.org/10.1016/j.aquabot.2007.12.007 (2008).Article 

    Google Scholar 
    Hamilton, S. E. & Casey, D. Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC-21). Glob. Ecol. Biogeogr. 25, 729–738. https://doi.org/10.1111/geb.12449 (2016).Article 

    Google Scholar 
    Friess, D. A. et al. The state of the world’s Mangrove forests: Past, present, and future. Annu. Rev. Environ. Resour. 44, 89–115. https://doi.org/10.1146/annurev-environ-101718-033302 (2019).Article 

    Google Scholar 
    Zeng, Y., Friess, D. A., Sarira, T. V., Siman, K. & Koh, L. P. Global potential and limits of mangrove blue carbon for climate change mitigation. Curr. Biol. 31, 1737-1743.e1733. https://doi.org/10.1016/j.cub.2021.01.070 (2021).Article 
    CAS 

    Google Scholar 
    zu Ermgassen, P. S. E. et al. Fishers who rely on mangroves: Modelling and mapping the global intensity of mangrove-associated fisheries. Estuar. Coast. Shelf Sci. 247, 106975. https://doi.org/10.1016/j.ecss.2020.106975 (2020).Article 

    Google Scholar 
    Walters, A. D. et al. Do hotspots fall within protected areas? A geographic approach to planning analysis of regional freshwater biodiversity. Freshw. Biol. 64, 2046–2056. https://doi.org/10.1111/fwb.13394 (2019).Article 

    Google Scholar 
    Blasco, F., Saenger, P. & Janodet, E. Mangroves as indicators of coastal change. CATENA 27, 167–178. https://doi.org/10.1016/0341-8162(96)00013-6 (1996).Article 

    Google Scholar 
    Gilman, E. L., Ellison, J., Duke, N. C. & Field, C. Threats to mangroves from climate change and adaptation options: A review. Aquat. Bot. 89, 237–250. https://doi.org/10.1016/j.aquabot.2007.12.009 (2008).Article 

    Google Scholar 
    Hamilton, S. Assessing the role of commercial aquaculture in displacing mangrove forest. Bull. Mar. Sci. 89, 585–601 (2013).Article 

    Google Scholar 
    Lovelock, C. E. et al. The vulnerability of Indo-Pacific mangrove forests to sea-level rise. Nature 526, 559–563. https://doi.org/10.1038/nature15538 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Richards Daniel, R. & Friess Daniel, A. Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012. Proc. Natl. Acad. Sci. 113, 344–349. https://doi.org/10.1073/pnas.1510272113 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Appeltans, W. et al. The magnitude of global marine species diversity. Curr. Biol. 22, 2189–2202. https://doi.org/10.1016/j.cub.2012.09.036 (2012).Article 
    CAS 

    Google Scholar 
    Ward, R. D., Friess, D. A., Day, R. H. & MacKenzie, R. A. Impacts of climate change on mangrove ecosystems: A region by region overview. Ecosyst. Health Sustain. 2, e01211. https://doi.org/10.1002/ehs2.1211 (2016).Article 

    Google Scholar 
    Van der Stocken, T., Vanschoenwinkel, B., Carroll, D., Cavanaugh, K. C. & Koedam, N. Mangrove dispersal disrupted by projected changes in global seawater density. Nat. Clim. Chang. 12, 685–691. https://doi.org/10.1038/s41558-022-01391-9 (2022).Article 
    ADS 

    Google Scholar 
    Alongi, D. M. The impact of climate change on Mangrove forests. Curr. Clim. Change Rep. 1, 30–39. https://doi.org/10.1007/s40641-015-0002-x (2015).Article 

    Google Scholar 
    Giri, C. et al. Status and distribution of mangrove forests of the world using earth observation satellite data. Glob. Ecol. Biogeogr. 20, 154–159. https://doi.org/10.1111/j.1466-8238.2010.00584.x (2011).Article 

    Google Scholar 
    Kristensen, E. Mangrove crabs as ecosystem engineers; with emphasis on sediment processes. J. Sea Res. 59, 30–43. https://doi.org/10.1016/j.seares.2007.05.004 (2008).Article 
    ADS 

    Google Scholar 
    Penha-Lopes, G. et al. Are fiddler crabs potentially useful ecosystem engineers in mangrove wastewater wetlands?. Mar. Pollut. Bull. 58, 1694–1703. https://doi.org/10.1016/j.marpolbul.2009.06.015 (2009).Article 
    CAS 

    Google Scholar 
    Sharifian, S., Kamrani, E. & Saeedi, H. Global biodiversity and biogeography of mangrove crabs: Temperature, the key driver of latitudinal gradients of species richness. J. Therm. Biol 92, 102692. https://doi.org/10.1016/j.jtherbio.2020.102692 (2020).Article 
    CAS 

    Google Scholar 
    Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).Article 

    Google Scholar 
    Guisan, A. & Zimmermann, N. E. Predictive habitat distribution models in ecology. Ecol. Model. 135, 147–186. https://doi.org/10.1016/S0304-3800(00)00354-9 (2000).Article 

    Google Scholar 
    Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435. https://doi.org/10.1111/ele.12189 (2013).Article 

    Google Scholar 
    Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models: With Applications in R. (Cambridge University Press, 2017).Luan, J., Zhang, C., Xu, B., Xue, Y. & Ren, Y. Modelling the spatial distribution of three Portunidae crabs in Haizhou Bay, China. PLoS ONE 13, e0207457. https://doi.org/10.1371/journal.pone.0207457 (2018).Article 
    CAS 

    Google Scholar 
    Kafash, A. et al. The Gray Toad-headed Agama, Phrynocephalus scutellatus, on the Iranian Plateau: The degree of niche overlap depends on the phylogenetic distance. Zool. Middle East 64, 47–54. https://doi.org/10.1080/09397140.2017.1401309 (2018).Article 

    Google Scholar 
    Yousefi, M., Shabani, A. A. & Azarnivand, H. Reconstructing distribution of the Eastern Rock Nuthatch during the Last Glacial Maximum and Last Interglacial. Avian Biol. Res. 13, 3–9. https://doi.org/10.1177/1758155919874537 (2019).Article 

    Google Scholar 
    De Rock, P. et al. Predicting large-scale habitat suitability for cetaceans off Namibia using MinxEnt. Mar. Ecol. Prog. Ser. 619, 149–167 (2019).Article 
    ADS 

    Google Scholar 
    Saeedi, H., Basher, Z. & Costello, M. J. Modelling present and future global distributions of razor clams (Bivalvia: Solenidae). Helgol. Mar. Res. 70, 23. https://doi.org/10.1186/s10152-016-0477-4 (2016).Article 

    Google Scholar 
    Bosso, L. et al. The rise and fall of an alien: why the successful colonizer Littorina saxatilis failed to invade the Mediterranean Sea. Biol. Invas. 24, 3169–3187. https://doi.org/10.1007/s10530-022-02838-y (2022).Article 

    Google Scholar 
    Moradmand, M. & Yousefi, M. Ecological niche modelling and climate change in two species groups of huntsman spider genus Eusparassus in the Western Palearctic. Sci. Rep. 12, 4138. https://doi.org/10.1038/s41598-022-08145-9 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Compton, T. J., Leathwick, J. R. & Inglis, G. J. Thermogeography predicts the potential global range of the invasive European green crab (Carcinus maenas). Divers. Distrib. 16, 243–255. https://doi.org/10.1111/j.1472-4642.2010.00644.x (2010).Article 

    Google Scholar 
    Kafash, A., Ashrafi, S. & Yousefi, M. Modeling habitat suitability of bats to identify high priority areas for field monitoring and conservation. Environ. Sci. Pollut. Res. 29, 25881–25891. https://doi.org/10.1007/s11356-021-17412-7 (2022).Article 

    Google Scholar 
    Leathwick, J. et al. Novel methods for the design and evaluation of marine protected areas in offshore waters. Conserv. Lett. 1, 91–102. https://doi.org/10.1111/j.1755-263X.2008.00012.x (2008).Article 

    Google Scholar 
    Charrua, A. B., Bandeira, S. O., Catarino, S., Cabral, P. & Romeiras, M. M. Assessment of the vulnerability of coastal mangrove ecosystems in Mozambique. Ocean Coast. Manag. 189, 105145. https://doi.org/10.1016/j.ocecoaman.2020.105145 (2020).Article 

    Google Scholar 
    Khajoei Nasab, F., Mehrabian, A. & Mostafavi, H. Mapping the current and future distributions of Onosma species endemic to Iran. J. Arid Land 12, 1031–1045. https://doi.org/10.1007/s40333-020-0080-z (2020).Article 

    Google Scholar 
    Allyn, A. J. et al. Comparing and synthesizing quantitative distribution models and qualitative vulnerability assessments to project marine species distributions under climate change. PLoS ONE 15, e0231595. https://doi.org/10.1371/journal.pone.0231595 (2020).Article 
    CAS 

    Google Scholar 
    Makki, T., Mostafavi, H., Matkan, A. & Aghighi, H. Modelling Climate-Change Impact on the Spatial Distribution of Garra Rufa (Heckel, 1843) (Teleostei: Cyprinidae). Iran. J. Sci. Technol. Trans. A: Sci. 45, 795–804. https://doi.org/10.1007/s40995-021-01088-2 (2021).Article 

    Google Scholar 
    Bolon, I. et al. What is the impact of snakebite envenoming on domestic animals? A nation-wide community-based study in Nepal and Cameroon. Toxicon: X 9–10, 100068. https://doi.org/10.1016/j.toxcx.2021.100068 (2021).Sharma, A., Dubey, V. K., Johnson, J. A., Rawal, Y. K. & Sivakumar, K. Is there always space at the top? Ensemble modeling reveals climate-driven high-altitude squeeze for the vulnerable snow trout Schizothorax richardsonii in Himalaya. Ecol. Ind. 120, 106900. https://doi.org/10.1016/j.ecolind.2020.106900 (2021).Article 

    Google Scholar 
    Yousefi, M., Naderloo, R. & Keikhosravi, A. Freshwater crabs of the Near East: Increased extinction risk from climate change and underrepresented within protected areas. Glob. Ecol. Conserv. 38, e02266. https://doi.org/10.1016/j.gecco.2022.e02266 (2022).Article 

    Google Scholar 
    Sheykhi Ilanloo, S. et al. Applying opportunistic observations to model current and future suitability of the Kopet Dagh Mountains for a Near Threatened avian scavenger. Avian Biol. Res. 14, 18–26. https://doi.org/10.1177/1758155920962750 (2020).Article 

    Google Scholar 
    Naderloo, R. Grapsoid crabs (Decapoda: Brachyura: Thoracotremata) of the Persian Gulf and the Gulf of Oman. Zootaxa 3048(1), 1. https://doi.org/10.11646/zootaxa.3048.1.1 (2011).Article 

    Google Scholar 
    Naderloo, R. Atlas of crabs of the Persian Gulf. (2017).Innocenti, G., Schubart, C. D. & Fratini, S. Description of Metopograpsus cannicci, new species, a pseudocryptic crab species from East Africa and the Western Indian Ocean (Decapoda: Brachyura: Grapsidae). Raffles Bull. Zool. (RBZ) 68, 619–628 (2020).
    Google Scholar 
    Hemmati, M. R., Shojaei, M. G., Taheri Mirghaed, A., Mashhadi Farahani, M. & Weigt, M. Food sources for camptandriid crabs in an arid mangrove ecosystem of the Persian Gulf: a stable isotope approach. Isotop. Environ. Health Stud. 57, 457–469. https://doi.org/10.1080/10256016.2021.1925665 (2021).Article 
    CAS 

    Google Scholar 
    Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101. https://doi.org/10.1038/nature09329 (2010).Article 
    ADS 
    CAS 

    Google Scholar 
    Kordas, R. L., Harley, C. D. G. & O’Connor, M. I. Community ecology in a warming world: The influence of temperature on interspecific interactions in marine systems. J. Exp. Mar. Biol. Ecol. 400, 218–226. https://doi.org/10.1016/j.jembe.2011.02.029 (2011).Article 

    Google Scholar 
    Hall, S. & Thatje, S. Temperature-driven biogeography of the deep-sea family Lithodidae (Crustacea: Decapoda: Anomura) in the Southern Ocean. Polar Biol. 34, 363–370. https://doi.org/10.1007/s00300-010-0890-0 (2011).Article 

    Google Scholar 
    Hannah, L. Climate Change Biology. Academic Press (2015).Ali, H. et al. Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan. PLoS ONE 16, e0260031. https://doi.org/10.1371/journal.pone.0260031 (2022).Article 
    CAS 

    Google Scholar 
    Yousefi, M. et al. Climate change is a major problem for biodiversity conservation: A systematic review of recent studies in Iran. Contemp. Probl. Ecol. 12, 394–403. https://doi.org/10.1134/S1995425519040127 (2019).Article 

    Google Scholar 
    Doney, S. C. et al. Climate Change Impacts on Marine Ecosystems. Ann. Rev. Mar. Sci. 4, 11–37. https://doi.org/10.1146/annurev-marine-041911-111611 (2011).Article 

    Google Scholar 
    Worm, B. & Lotze, H. K. in Climate Change (Second Edition) (ed Trevor M. Letcher) 195–212 (Elsevier, 2016).Ramírez, F., Afán, I., Davis, L. S. & Chiaradia, A. Climate impacts on global hot spots of marine biodiversity. Sci. Adv. 3, e1601198. https://doi.org/10.1126/sciadv.1601198 (2017).Article 
    ADS 

    Google Scholar 
    Worm, B. et al. Impacts of Biodiversity Loss on Ocean Ecosystem Services. Science 314, 787–790. https://doi.org/10.1126/science.1132294 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Lester, S. E. et al. Biological effects within no-take marine reserves: a global synthesis. Mar. Ecol. Prog. Ser. 384, 33–46 (2009).Article 
    ADS 

    Google Scholar 
    Daru, B. H. & le Roux, P. C. Marine protected areas are insufficient to conserve global marine plant diversity. Glob. Ecol. Biogeogr. 25, 324–334. https://doi.org/10.1111/geb.12412 (2016).Article 

    Google Scholar 
    Sala, E. et al. Protecting the global ocean for biodiversity, food and climate. Nature https://doi.org/10.1038/s41586-021-03371-z (2021).Article 

    Google Scholar 
    Embling, C. B. et al. Using habitat models to identify suitable sites for marine protected areas for harbour porpoises (Phocoena phocoena). Biol. Cons. 143, 267–279. https://doi.org/10.1016/j.biocon.2009.09.005 (2010).Article 

    Google Scholar 
    Magris, R. A. & Déstro, G. F. G. Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil. Braz. J. Oceanogr. 58, 57–68 (2010).Article 

    Google Scholar 
    Welch, H., Pressey, R. L. & Reside, A. E. Using temporally explicit habitat suitability models to assess threats to mobile species and evaluate the effectiveness of marine protected areas. J. Nat. Conserv. 41, 106–115. https://doi.org/10.1016/j.jnc.2017.12.003 (2018).Article 

    Google Scholar 
    Rhoden, C. M., Peterman, W. E. & Taylor, C. A. Maxent-directed field surveys identify new populations of narrowly endemic habitat specialists. PeerJ 5, e3632–e3632. https://doi.org/10.7717/peerj.3632 (2017).Article 

    Google Scholar 
    Ancillotto, L., Mori, E., Bosso, L., Agnelli, P. & Russo, D. The Balkan long-eared bat (Plecotus kolombatovici) occurs in Italy—First confirmed record and potential distribution. Mamm. Biol. 96, 61–67. https://doi.org/10.1016/j.mambio.2019.03.014 (2019).
    Article 

    Google Scholar 
    Imtiyaz, B. B., Sweta, P. D., Prakash, K. K. Threats to marine biodiversity. Mar. Biodivers.: Present Status Prospects (2011).Robinson, N. M., Nelson, W. A., Costello, M. J., Sutherland, J. E. & Lundquist, C. J. A systematic review of marine-based species distribution models (SDMs) with recommendations for best practice. Front. Mar. Sci. 4, 421 (2017).Article 

    Google Scholar 
    Fabri-Ruiz, S., Danis, B., David, B. & Saucède, T. Can we generate robust species distribution models at the scale of the Southern Ocean?. Divers. Distrib. 25, 21–37. https://doi.org/10.1111/ddi.12835 (2019).Article 

    Google Scholar 
    Maxwell, D. L., Stelzenmüller, V., Eastwood, P. D. & Rogers, S. I. Modelling the spatial distribution of plaice (Pleuronectes platessa), sole (Solea solea) and thornback ray (Raja clavata) in UK waters for marine management and planning. J. Sea Res. 61, 258–267. https://doi.org/10.1016/j.seares.2008.11.008 (2009).Article 
    ADS 

    Google Scholar 
    Marshall, C. E., Glegg, G. A. & Howell, K. L. Species distribution modelling to support marine conservation planning: The next steps. Mar. Policy 45, 330–332. https://doi.org/10.1016/j.marpol.2013.09.003 (2014).Article 

    Google Scholar 
    GBIF. GBIF Occurrence Download https://doi.org/10.15468/dl.khpu28. GBIF (2021).Spalding, M. D. et al. Marine ecoregions of the world: A bioregionalization of coastal and shelf areas. Bioscience 57, 573–583. https://doi.org/10.1641/B570707 (2007).Article 

    Google Scholar 
    Basher, Z., Bowden, D. A. & Costello, M. J. Global marine environment datasets (GMED). World Wide Web Electron. Publ. 14, 1 (2018).
    Google Scholar 
    Barnes, D. Ecology of subtropical hermit crabs in SW Madagascar: short-range migrations. Mar. Biol. 142, 549–557. https://doi.org/10.1007/s00227-002-0968-5 (2003).Article 

    Google Scholar 
    Naimullah, M. et al. Association of environmental factors in the Taiwan Strait with distributions and habitat characteristics of three swimming crabs. Remote Sens. 12, 1. https://doi.org/10.3390/rs12142231 (2020).Article 

    Google Scholar 
    Malvé, M. E., Rivadeneira, M. M. & Gordillo, S. Northward range expansion of the European green crab Carcinus maenas in the SW Atlantic: a synthesis after ~20 years of invasion history. bioRxiv, 2020.2011.2004.368761, doi:https://doi.org/10.1101/2020.11.04.368761 (2020).Merow, C., Smith, M. J. & Silander, J. A. Jr. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36, 1058–1069. https://doi.org/10.1111/j.1600-0587.2013.07872.x (2013).Article 

    Google Scholar 
    Naimi, B. & Araújo, M. B. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography 39, 368–375. https://doi.org/10.1111/ecog.01881 (2016).Article 

    Google Scholar 
    Team, R. C. R: A Language and Environment for Statistical Computing (2020).Fielding, A. H. & Bell, J. F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 24, 38–49. https://doi.org/10.1017/S0376892997000088 (1997).Article 

    Google Scholar 
    Swets John, A. Measuring the Accuracy of Diagnostic Systems. Science 240, 1285–1293. https://doi.org/10.1126/science.3287615 (1988).Article 
    ADS 
    MathSciNet 
    MATH 

    Google Scholar 
    Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: an open-source release of Maxent. Ecography 40, 887–893. https://doi.org/10.1111/ecog.03049 (2017).Article 

    Google Scholar 
    Hijmans, R. J. raster: Geographic Data Analysis and Modeling. R package version 3.3–7 (2020).UNEP-WCMC and IUCN. Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM). UNEP-WCMC and IUCN (2021). More

  • in

    Improving access to aquatic foods

    Bennett, A. et al. Nat. Food https://doi.org/10.1038/s43016-022-00642-4 (2022).Article 

    Google Scholar 
    Simmance, F. A. et al. Nat. Commun. 3, 174 (2022).
    Google Scholar 
    Kolding, J., van Zwieten, P., Martin, F., Funge-Smith, S. & Poulain, F. Freshwater Small Pelagic Fish and Their Fisheries in the Major African Lakes and Reservoirs in Relation to Food Security and Nutrition (Food and Agriculture Organization of the United Nations, 2019).Pradhan, S. K., Nayak, P. K. & Armitage, D. Curr. Res. Environ. Sustain. 4, 100128 (2022).Article 

    Google Scholar 
    Byrd, K. A., Pincus, L., Pasqualino, M. M., Muzofa, F. & Cole, S. M. Matern. Child Nutr. 17, e13192 (2021).Article 

    Google Scholar 
    Chiwaula, L. S., Chirwa, G. C., Binauli, L. S., Banda, J. & Nagoli, J. Agric. Food Econ. 6, 1–15 (2018).Article 

    Google Scholar 
    Cole, S. M. et al. Ecol. Soc. 23, 18 (2018).Article 

    Google Scholar 
    Manyungwa, C. L., Hara, M. M. & Chimatiro, S. K. Marit. Stud. 18, 275–285 (2019).Article 

    Google Scholar 
    Coates, J. et al. Food Policy 81, 82–94 (2018).Article 

    Google Scholar 
    Stevens, G. A. et al. Lancet Glob. Health 10, e1590–e1599 (2022).Article 

    Google Scholar 
    Hicks, C. C. et al. Nat. Food 3, 851–861 (2022).Article 

    Google Scholar  More

  • in

    Logged tropical forests have amplified and diverse ecosystem energetics

    Human-modified forests, such as selectively logged forests, are often characterized as degraded ecosystems because of their altered structure and low biomass. The concept of ecosystem degradation can be a double-edged sword. It rightly draws attention to the conservation value of old-growth systems and the importance of ecosystem restoration. However, it can also suggest that human-modified ecosystems are of low ecological value and therefore, in some cases, suitable for conversion to agriculture (such as oil palm plantations) and other land uses3,4,5.Selectively logged and other forms of structurally altered forests are becoming the prevailing vegetation cover in much of the tropical forest biome2. Such disturbance frequently leads to a decline in old-growth specialist species1, and also in non-specialist species in some contexts6,7,8. However, species-focused biodiversity metrics are only one measure of ecosystem vitality and functionality, and rarely consider the collective role that suites of species play in maintaining ecological functions9.An alternative approach is to focus on the energetics of key taxonomic groups, and the number and relative dominance of species contributing to each energetic pathway. Energetic approaches to examining ecosystem structure and function have a long history in ecosystem ecology10. Virtually all ecosystems are powered by a cascade of captured sunlight through an array of autotroph tissues and into hierarchical assemblages of herbivores, carnivores and detritivores. Energetic approaches shine light on the relative significance of energy flows among key taxa and provide insight into the processes that shape biodiversity and ecosystem function. The common currency of energy enables diverse guilds and taxa to be compared in a unified and physically meaningful manner: dominant energetic pathways can be identified, and the resilience of each pathway to the loss of individual species can be assessed. Quantitative links can then be made between animal communities and the plant-based ecosystem productivity on which they depend. The magnitude of energetic pathways in particular animal groups can often be indicators of key associated ecosystem processes, such as nutrient cycling, seed dispersal and pollination, or trophic factors such as intensity of predation pressure or availability of resource supply, all unified under the common metric of energy flux11,12.Energetics approaches have rarely been applied in biodiverse tropical ecosystems because of the range of observations they require11,12,13. Such analyses rely on: population density estimates for a very large number of species; understanding of the diet and feeding behaviour of the species; and reliable estimation of net primary productivity (NPP). Here we take advantage of uniquely rich datasets to apply an energetics lens to examine and quantify aspects of the ecological function and vitality of habitats in Sabah, Malaysia, that comprise old-growth forests, logged forest and oil palm plantation (Fig. 1 and Extended Data Fig. 1). Our approach is to calculate the short-term equilibrium production or consumption rates of food energy by specific species, guilds or taxonomic groups. We focus on three taxonomic groups (plants, birds and mammals) that are frequently used indicators of biodiversity and are relatively well understood ecologically.Fig. 1: Maps of the study sites in Sabah, Borneo.a–d, Maps showing locations of NPP plots and biodiversity surveys in old-growth forest, logged forest and oil palm plantations in the Stability of Altered Forest Ecosystems Project landscape (a), Maliau Basin (b), Danum Valley (c) and Sepilok (d). The inset in a shows the location of the four sites in Sabah. The shade of green indicates old-growth (dark green), twice-logged (intermediate green) or heavily logged (light green) forests. The camera and trap grid includes cameras and small mammal traps. White areas indicate oil palm plantations.Full size imageWe are interested in the fraction of primary productivity consumed by birds and mammals, and how it varies along the disturbance gradient, and how and why various food energetic pathways in mammals and birds, and the diversity of species contributing to those pathways, vary along the disturbance gradient. To estimate the density of 104 mammal and 144 bird species in each of the three habitat types, we aggregated data from 882 camera sampling locations (a total of 42,877 camera trap nights), 508 bird point count locations, 1,488 small terrestrial mammal trap locations (34,058 live-trap nights) and 336 bat trap locations (Fig. 1 and Extended Data Fig. 1). We then calculated daily energetic expenditure for each species based on their body mass, assigned each species to a dietary group and calculated total food consumption in energy units. For primary productivity, we relied on 34 plot-years (summation of plots multiplied by the number of years each plot is monitored) of measurements of the key components of NPP (canopy litterfall, woody growth, fine root production) using the protocols of the Global Ecosystem Monitoring Network14,15,16 across old-growth (n = 4), logged (n = 5) and oil palm (n = 1) plots. This dataset encompasses more than 14,000 measurements of litterfall, 20,000 tree diameter measurements and 2,700 fine root samples.Overall bird species diversity is maintained across the disturbance gradient and peaks in the logged forest; for mammals, there is also a slight increase in the logged forest, followed by rapid decline in the oil palm (Fig. 2b,c). Strikingly, both bird and mammal biomass increases substantially (144% and 231%, respectively) in the logged forest compared to the old-growth forest, with mammals contributing about 75% of total (bird plus mammal) biomass in both habitat types (Fig. 2b,c).Fig. 2: Variation of ecosystem energetics along the disturbance gradient from old-growth forest through logged forest to oil palm.a, Total NPP along the gradient (mean of intensive 1-ha plots; n = 4 for old growth (OG), n = 5 for logged and n = 1 for oil palm (OP); error bars are 95% confidence intervals derived from propagated uncertainty in the individually measured NPP components), with individual plot data points overlaid. b,c, Total body mass (bars, left axis) and number of species counted (blue dots and line, right axis) of birds (b) and mammals (c). d,e, Total direct energetic food intake by birds (d) and mammals (e). f,g, Percentage of NPP directly consumed by birds (f) and mammals (g). In b–e, body mass and energetics were estimated for individual bird and mammal species, with the bars showing the sum. Error bars denote 95% confidence intervals derived from 10,000 Monte Carlo simulation estimates incorporating uncertainty in body mass, population density, the daily energy expenditure equation, assimilation efficiency of the different food types, composition of the diet of each species and NPP. In f,g, the grey bars indicate direct consumption of NPP, white bars denote the percentage of NPP indirectly supporting bird and mammal food intake when the mean trophic level of consumed invertebrates is assumed to be 2.5, with the error bars denoting assumed mean trophic levels of 2.4 and 2.6. Note the log scale of the y axis in f,g. Numbers for d,e provided in Supplementary Data Tables 1, 2.Full size imageThe total flow of energy through consumption is amplified across all energetic pathways by a factor of 2.5 (2.2–3.0; all ranges reported are 95% confidence intervals) in logged forest relative to old-growth forest. In all three habitat types, total energy intake by birds is much greater than by mammals (Fig. 2d,e and Extended Data Table 1). Birds account for 67%, 68% and 90% of the total direct consumption by birds and mammals combined in old-growth forests, logged forests and oil palm, respectively. Although mammal biomass is higher than bird biomass in the old-growth and logged forests, the metabolism per unit mass is much higher in birds because of their small body size; hence, in terms of the energetics and consumption rates, the bird community dominates. The total energy intake by birds alone increases by a factor of 2.6 (2.1–3.2) in the logged forest relative to old-growth forest. This is mainly driven by a 2.5-fold (1.7–2.8) increase in foliage-gleaning insectivory (the dominant energetic pathway), and most other feeding guilds also show an even larger increase (Figs. 2d and 3). However, total bird energy intake in the oil palm drops back to levels similar to those in the old-growth forest, with a collapse in multiple guilds. For mammals, there is a similar 2.4-fold (1.9–3.2) increase in total consumption when going from old-growth to logged forest, but this declines sharply in oil palm plantation. Most notable is the 5.7-fold (3.2–10.2) increase in the importance of terrestrial mammal herbivores in the logged relative to old-growth forests. All four individual old-growth forest sites show consistently lower bird and mammal energetics than the logged forests (Extended Data Fig. 5).Fig. 3: Magnitude and species diversity of energetic pathways in old-growth forest, logged forest and oil palm.The size of the circles indicates the magnitude of energy flow, and the colour indicates birds or mammals. S, number of species; E, ESWI, an index of species redundancy and, therefore, resilience (high values indicate high redundancy; see main text). For clarity, guilds with small energetic flows are not shown, but are listed in Supplementary Data 4. Images created by J. Bentley.Full size imageThe fraction of NPP flowing through the bird and mammal communities increases by a factor of 2.1 (1.5–3.0) in logged forest relative to old-growth forest. There is very little increase in NPP in logged relative to old-growth forests (Fig. 2a) because increased NPP in patches of relatively intact logged forest is offset by very low productivity in more structurally degraded areas such as former logging platforms14,15. In oil palm plantations, oil palm fruits account for a large proportion of NPP, although a large fraction of these is harvested and removed from the ecosystem17. As a proportion of NPP, 1.62% (1.35–2.13%) is directly consumed by birds and mammals in the old-growth forest; this rises to 3.36% (2.57–5.07%) in the logged forest but drops to 0.89% (0.57–1.44%) in oil palm (Fig. 2f,g and Extended Data Table 2).If all invertebrates consumed are herbivores or detritivores (that is, at a trophic level of 2.0), and trophic efficiency is 10% (ref. 10), the total amount of NPP supporting the combined bird and mammal food intake would be 9%, 16% and 5% for old-growth forest, logged forest and oil palm, respectively. However, if the mean trophic level of consumed invertebrates is 2.5 (that is, a mix of herbivores and predators), the corresponding proportions would be 27%, 51% and 17% (Fig. 2f,g). As insectivory is the dominant feeding mode for the avian community, these numbers are dominated by bird diets. For birds in the old-growth forests, 0.35% of NPP supports direct herbivory and frugivory, but around 22% of NPP (assumed invertebrate trophic level 2.5) is indirectly required to support insectivory. The equivalent numbers for birds in logged forest are 0.83% and 46%. Hence, birds account for a much larger indirect consumption of NPP. Bird diet studies in old-growth and logged forest in the region suggest that consumed invertebrates have a mean trophic level of 2.5 (ref. 18; K. Sam, personal communication), indicating that the higher-end estimates of indirect NPP consumption (that is, around 50% in logged forests) are plausible.It is interesting to compare such high fractions of NPP to direct estimates of invertebrate herbivory. Scans of tree leaf litter from these forests suggest that just 7.0% of tree canopy leaf area (1–3% of total NPP) is removed by tree leaf herbivory14,16, but such estimates do not include other pathways available to invertebrates, including herbivory of the understorey, aboveground and belowground sap-sucking, leaf-mining, fruit- and wood-feeding, and canopy, litter and ground-layer detritivory. An increase in invertebrate biomass and herbivory in logged forest compared to old-growth forest has previously been reported in fogging studies in this landscape19. Such high levels of consumption of NPP by invertebrates could have implications on ecosystem vegetation biomass production, suggesting, first, that invertebrate herbivory has a substantial influence on recovery from logging and, second, that insectivorous bird densities may exert substantial indirect controls on ecosystem recovery.The distributions of energy flows among feeding guilds are remarkably stable among habitat types (Fig. 3), indicating that the amplified energy flows in the logged forests do not distort the overall trophic structure of vertebrate communities. Overall bird diet energetics are dominated by insectivory, which accounts for a strikingly invariant 66%, 63% and 66% of bird energetic consumption in old-growth forest, logged forest and oil palm, respectively. Foliage-gleaning dominates as a mode of invertebrate consumption in all three habitat types, with frugivory being the second most energetically important feeding mode (26%, 27% and 19%, respectively). Mammal diet is more evenly distributed across feeding guilds, but frugivory (31%, 30%, 30%) and folivory (24%, 38%, 26%) dominate. Small mammal insectivores are probably under-sampled (see Methods) so the contribution of mammal insectivory may be slightly greater than that estimated here. The apparent constancy of relative magnitude of feeding pathways across the intact and disturbed ecosystems is noteworthy and not sensitive to plausible shifts in feeding behaviour between habitat types (see Supplementary Discussion). There is no evidence of a substantial shift in dominant feeding guild: the principal feeding pathways present in the old-growth forest are maintained in the logged forest.When examining change at species level in the logged forests, the largest absolute increases in bird food consumption were in arboreal insectivores and omnivores (Fig. 4a and Extended Data Fig. 2a). In particular, this change was characterized by large increases in the abundance of bulbul species (Pycnonotus spp.). No bird species showed a significant or substantial reduction in overall energy consumption. In the oil palm plantation, total food consumption by birds was less than in logged forests, but similar to that in old-growth forests. However, this was driven by very high abundance of a handful of species, notably a single arboreal omnivore (yellow-vented bulbul Pycnonotus goiavier) and three arboreal insectivores (Mixornis bornensis, Rhipidura javanica, Copsychus saularis), whereas energy flows through most other bird species were greatly reduced (Fig. 4b and Extended Data Fig. 2b).Fig. 4: Changes in energy consumption by species in logged forest and oil palm relative to old-growth forest.a,b, Changes in energy consumption by species in logged forest relative to old-growth forest (a) and in oil palm relative to old-growth forest (b). The 20 species experiencing the largest increase (red) and decrease (blue) in both habitat types are shown. Bird species are shown in a lighter tone and mammal species are shown in a darker tone. The error bars denote 95% confidence intervals, derived from 10,000 Monte Carlo simulation estimates incorporating uncertainty in body mass, population density, the daily energy expenditure equation, assimilation efficiency of the different food types and composition of the diet of each species.Full size imageFor mammals, the increase in consumption in logged forests is dominated by consumption by large terrestrial herbivores increasing by a factor of 5.7 (3.2–10.2), particularly sambar deer (Rusa unicolor) and Asian elephant (Elephas maximus; Fig. 4a and Extended Data Figs. 2b and 3), along with that by small omnivores, predominantly rodents (native spiny rats, non-native black rat; Fig. 4). A few rainforest species show a strong decline (for example, greater mouse-deer Tragulus napu and brown spiny rat Maxomys rajah). In the oil palm, most mammal species collapse (Fig. 4b) and the limited consumption is dominated by a few disturbance-tolerant habitat generalists (for example, red muntjac Muntiacus muntjak, black rat Rattus rattus, civets), albeit these species are at lower densities than observed in old-growth forest (Extended Data Fig. 2).With very few exceptions, the amplified energy flows in logged forest seem to retain the same level of resilience as in old-growth forest. The diversity and dominance of species within any pathway can be a measure of the resilience of that pathway to loss of species. We assessed energetic dominance within individual pathways by defining an energetic Shannon–Wiener index (ESWI) to examine distribution of energy flow across species; low ESWI indicates a pathway with high dependence on a few species and hence potential vulnerability (Fig. 3). The overall ESWI across guilds does not differ between the old-growth and logged forest (t2,34 = −0.363, P = 0.930), but does decline substantially from old-growth forest to oil palm (t2,34 = −3.826, P = 0.0015), and from logged forest to oil palm (t2,34 = −3.639, P = 0.0025; linear mixed-effects models, with habitat type as fixed effect and guild as random effect; for model coefficients see Supplementary Table 3).Hence, for birds, the diversity of species contributing to dominant energetic pathways is maintained in the transition from old-growth to logged forests but declines substantially in oil palm. Mammals generally show lower diversity and ESWI than birds, but six out of ten feeding guilds maintain or increase ESWI in logged forest relative to the old-growth forests but collapse in oil palm (Fig. 3). Terrestrial herbivory is the largest mammal pathway in the logged forest but is dependent on only four species and is probably the most vulnerable of the larger pathways: a few large mammals (especially sambar deer) play a dominant terrestrial herbivory role in the logged forest. In parallel, bearded pigs (Sus barbatus), the only wild suid in Borneo, form an important and functionally unique component of the terrestrial omnivory pathway. These larger animals are particularly sensitive to anthropogenic pressures such as hunting, or associated pathogenic pressures as evidenced by the recent precipitous decline of the bearded pig in Sabah due to an outbreak of Asian swine fever (after our data were collected)20.Vertebrate populations across the tropics are particularly sensitive to hunting pressure21. Our study site has little hunting, but as a sensitivity analysis we explored the energetic consequences of 50% reduction in population density of those species potentially affected by targeted and/or indiscriminate hunting (Extended Data Fig. 4). Targeted hunted species include commercially valuable birds, and gun-hunted mammals (bearded pig, ungulates, banteng and mammals with medicinal value). Indiscriminately hunted species include birds and mammals likely to be trapped with nets and snares. Hunting in the logged forests lowers both bird and mammal energy flows but still leaves them at levels higher than in faunally intact old-growth forests. Such hunting brings bird energetics levels close to (but still above) those of old-growth forests. For mammals, however, even intensively hunted logged forests seem to maintain higher energetic flows than the old-growth forests. Hence, only very heavy hunting is likely to ‘offset’ the amplified energetics in the logged forest.The amplified energetic pathways in our logged forest probably arise as a result of bottom-up trophic factors including increased resource supply, palatability and accessibility. The more open forest structure in logged forest results in more vegetation being near ground level22,23 and hence more accessible to large generalist mammal herbivores, which show the most striking increase of the mammal guilds. The increased prioritization by plants of competition for light and therefore rapid vegetation growth strategies in logged forests results in higher leaf nutrient content and reduced leaf chemical defences against herbivory24,25, along with higher fruiting and flowering rates19 and greater clumping in resource supply9. This increased resource availability and palatability probably supports high invertebrate and vertebrate herbivore densities25. The act of disturbance displaces the ecosystem from a conservative chemically defended state to a more dynamic state with amplified energy and nutrient flow, but not to an extent that causes heavy disruption in animal community composition. Top-down trophic factors might also play a role in amplifying the energy flows in intermediate trophic levels, through mechanisms such as increased protection of ground-dwelling or nesting mammals and birds from aerial predators in the dense vegetation ground layer. This might partially explain the increased abundance of rodents, but there is little evidence of trophic release at this site because of the persisting high density of mammal carnivores26. Overall, the larger number of bottom-up mechanisms and surge in invertebrate consumption suggest that increased resource supply and palatability largely explains the amplification of consumption pathways in the logged forest. An alternative possibility is that the amplified vertebrate energetics do not indicate amplified overall animal energetics but rather a large diversion of energy from unmeasured invertebrate predation pathways (for example, parasitoids); this seems unlikely but warrants further exploration.Oil palm plantations show a large decline in the proportion of NPP consumed by mammals and birds compared to logged forests12. Mammal populations collapse because they are more vulnerable and avoid humans, and there is no suite of mammal generalists that can step in27,28. Birds show a more modest decline, to levels similar to those observed in old-growth forests, as there is a broad suite of generalist species that are able to adapt to and exploit the habitat types across the disturbance gradient, and because their small size and mobility render them less sensitive to human activity29. There is a consistent decline in the oil palm in ESWI for birds and especially for mammals, indicating a substantial increase in ecosystem vulnerability in many pathways.In conclusion, our analysis demonstrates the tremendously dynamic and ecologically vibrant nature of the studied logged forests, even heavily and repeatedly logged forests such as those found across Borneo. It is likely that the patterns, mechanisms and basic ecological energetics we describe are general to most tropical forests; amplification of multiple ecosystem processes after logging has also been reported for logged forests in Kenya9, but similar detailed analyses are needed for a range of tropical forests to elucidate the importance of biogeographic, climatic or other factors. We stress that our findings do not diminish the importance of protecting structurally intact old-growth forests, but rather question the meaning of degradation by shining a new light on the ecological value of logged and other structurally ‘degraded’ forests, reinforcing their significance to the conservation agenda30. We have shown that a wide diversity of species not only persist but thrive in the logged forest environment. Moreover, such ecological vibrancy probably enhances the prospects for ecosystem structural recovery. In terms of faunal intactness, our study landscape is close to a best-case scenario because hunting pressures were low. If logged forests can be protected from heavy defaunation, our analysis demonstrates that they can be vibrant ecosystems, providing many key ecosystem functions at levels much higher than in old-growth forests. Conservation of logged forest landscapes has an essential role to play in the in the protection of global biodiversity and biosphere function. More

  • in

    An energetic look at the life in logged forests

    Putz, F. E. et al. Conserv. Lett. 5, 296–303 (2012).Article 

    Google Scholar 
    Blaser, J., Sarre, A., Poore, D. & Johnson, S. Status of Tropical Forest Management 2011. ITTO Tech. Ser. No. 38 (International Tropical Timber Organization, 2011); available at https://go.nature.com/3usq2an
    Google Scholar 
    Malhi, Y. et al. Nature https://doi.org/10.1038/s41586-022-05523-1 (2022).Article 

    Google Scholar 
    Zwerts, J. A. et al. Conserv. Sci. Pract. 3, e568 (2021).Article 

    Google Scholar 
    Wilkie, D. S., Bennett, E. L., Peres, C. A. & Cunningham, A. A. Ann. N. Y. Acad. Sci. 1223, 120–128 (2011).Article 
    PubMed 

    Google Scholar 
    Putz, F. E., Blate, G. M., Redford, K. H., Fimbel, R. & Robinson, J. Conserv. Biol. 15, 7–20 (2001).Article 

    Google Scholar  More

  • in

    Biodiversity–stability relationships strengthen over time in a long-term grassland experiment

    Doak, D. F. et al. The statistical inevitability of stability‐diversity relationships in community ecology. Am. Nat. 151, 264–276 (1998).Article 
    CAS 

    Google Scholar 
    Schläpfer, F. & Schmid, B. Ecosystem effects of biodiversity: a classification hypotheses and exploration of empirical results. Ecol. Appl. 9, 893–912 (1999).Article 

    Google Scholar 
    Lehman, C. L. & Tilman, D. Biodiversity, stability, and productivity in competitive communities. Am. Nat. 156, 534–552 (2000).Article 

    Google Scholar 
    Allan, E. et al. More diverse plant communities have higher functioning over time due to turnover in complementary dominant species. Proc. Natl Acad. Sci. USA 108, 17034–17039 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Isbell, F. et al. High plant diversity is needed to maintain ecosystem services. Nature 477, 199–202 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Wagg, C. et al. Plant diversity maintains long-term ecosystem productivity under frequent drought by increasing short-term variation. Ecology 98, 2952–2961 (2017).Article 

    Google Scholar 
    Isbell, F. et al. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature 526, 574–577 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Reich, P. B. et al. Impacts of biodiversity loss escalate through time as redundancy fades. Science 336, 589–592 (2012).Article 
    ADS 
    CAS 

    Google Scholar 
    Guerrero-Ramírez, N. R. et al. Diversity-dependent temporal divergence of ecosystem functioning in experimental ecosystems. Nat. Ecol. Evol. 1, 1639–1642 (2017).Article 

    Google Scholar 
    Meyer, S. T. et al. Effects of biodiversity strengthen over time as ecosystem functioning declines at low and increases at high biodiversity. Ecosphere 7, e01619 (2016).Article 

    Google Scholar 
    Huang, Y. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Bongers, F. J. et al. Functional diversity effects on productivity increase with age in a forest biodiversity experiment. Nat. Ecol. Evol. 5, 1594–1603 (2021).Article 

    Google Scholar 
    Weisser, W. W. et al. Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: Patterns, mechanisms, and open questions. Basic Appl. Ecol. 23, 1–73 (2017).Article 

    Google Scholar 
    Guerrero-Ramírez, N. R., Reich, P. B., Wagg, C., Ciobanu, M. & Eisenhauer, N. Diversity-dependent plant–soil feedbacks underlie long-term plant diversity effects on primary productivity. Ecosphere 10, e02704 (2019).Article 

    Google Scholar 
    Eisenhauer, N. The shape that matters: how important is biodiversity for ecosystem functioning. Sci. China Life Sci. 65, 651–653 (2022).Article 

    Google Scholar 
    Cardinale, B. J. et al. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104, 18123–18128 (2007).Article 
    ADS 
    CAS 

    Google Scholar 
    Marquard, E. et al. Plant species richness and functional composition drive overyielding in a six-year grassland experiment. Ecology 90, 3290–3302 (2009).Article 

    Google Scholar 
    Zuppinger-Dingley, D. et al. Selection for niche differentiation in plant communities increases biodiversity effects. Nature 515, 108–111 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).Article 
    ADS 
    CAS 

    Google Scholar 
    Wang, S. et al. How complementarity and selection affect the relationship between ecosystem functioning and stability. Ecology 102, e03347 (2021).Article 

    Google Scholar 
    Yan, Y. et al. Mechanistic links between biodiversity effects on ecosystem functioning and stability in a multi-site grassland experiment. J. Ecol. 109, 3370–3378 (2021).Article 

    Google Scholar 
    Barry, K. E. et al. The future of complementarity: disentangling causes from consequences. Trends Ecol. Evol. 34, 167–180 (2019).Article 

    Google Scholar 
    Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl Acad. Sci. USA 96, 1463–1468 (1999).Article 
    ADS 
    CAS 

    Google Scholar 
    Gonzalez, A. & Loreau, M. The causes and consequences of compensatory dynamics in ecological communities. Annu. Rev. Ecol. Evol. Syst. 40, 393–414 (2009).Article 

    Google Scholar 
    Thibaut, L. M. & Connolly, S. R. Understanding diversity–stability relationships: towards a unified model of portfolio effects. Ecol. Lett. 16, 140–150 (2013).Article 

    Google Scholar 
    Craven, D. et al. Multiple facets of biodiversity drive the diversity–stability relationship. Nat. Ecol. Evol. 2, 1579–1587 (2018).Article 

    Google Scholar 
    Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Loreau, M. Biodiversity and Ecosystem Functioning (Princeton Univ. Press,2010).Loreau, M. & de Mazancourt, C. Biodiversity and ecosystem stability: a synthesis of underlying mechanisms. Ecol. Lett. 16, 106–115 (2013).Article 

    Google Scholar 
    Isbell, F. et al. Quantifying effects of biodiversity on ecosystem functioning across times and places. Ecol. Lett. 21, 763–778 (2018).Article 

    Google Scholar 
    Maron, J. L., Marler, M., Klironomos, J. N. & Cleveland, C. C. Soil fungal pathogens and the relationship between plant diversity and productivity. Ecol. Lett. 14, 36–41 (2011).Article 

    Google Scholar 
    Schnitzer, S. A. et al. Soil microbes drive the classic plant diversity–productivity pattern. Ecology 92, 296–303 (2011).Article 

    Google Scholar 
    Marquard, E. et al. Changes in the abundance of grassland species in monocultures versus mixtures and their relation to biodiversity effects. PLoS ONE 8, e75599 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Roscher, C. et al. Identifying population- and community-level mechanisms of diversity–stability relationships in experimental grasslands. J. Ecol. 99, 1460–1469 (2011).Article 

    Google Scholar 
    Civitello, D. J. et al. Biodiversity inhibits parasites: broad evidence for the dilution effect. Proc. Natl Acad. Sci. USA 112, 8667–8671 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Kulmatiski, A., Beard, K. H. & Heavilin, J. Plant–soil feedbacks provide an additional explanation for diversity–productivity relationships. Proc. R. Soc. B 279, 3020–3026 (2012).Article 

    Google Scholar 
    van Moorsel, S. J. et al. Co-occurrence history increases ecosystem stability and resilience in experimental plant communities. Ecology 102, e03205 (2021).Article 

    Google Scholar 
    Schöb, C., Brooker, R. W. & Zuppinger-Dingley, D. Evolution of facilitation requires diverse communities. Nat. Ecol. Evol. 2, 1381–1385 (2018).Article 

    Google Scholar 
    Temperton, V. M., Mwangi, P. N., Scherer-Lorenzen, M., Schmid, B. & Buchmann, N. Positive interactions between nitrogen-fixing legumes and four different neighbouring species in a biodiversity experiment. Oecologia 151, 190–205 (2007).Article 
    ADS 

    Google Scholar 
    Furey, G. N. & Tilman, D. Plant biodiversity and the regeneration of soil fertility. Proc. Natl Acad. Sci. USA 118, e2111321118 (2021).Article 
    CAS 

    Google Scholar 
    Gubsch, M. et al. Foliar and soil δ15N values reveal increased nitrogen partitioning among species in diverse grassland communities. Plant Cell Environ. 34, 895–908 (2011).Article 
    CAS 

    Google Scholar 
    Roscher, C., Schmid, B., Buchmann, N., Weigelt, A. & Schulze, E.-D. Legume species differ in the responses of their functional traits to plant diversity. Oecologia 165, 437–452 (2011).Article 
    ADS 

    Google Scholar 
    Eisenhauer, N. et al. Plant diversity effects on soil microorganisms support the singular hypothesis. Ecology 91, 485–496 (2010).Article 
    CAS 

    Google Scholar 
    Fornara, D. A. & Tilman, D. Plant functional composition influences rates of soil carbon and nitrogen accumulation. J. Ecol. 96, 314–322 (2008).Article 
    CAS 

    Google Scholar 
    Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 6707 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Xu, S. et al. Species richness promotes ecosystem carbon storage: evidence from biodiversity-ecosystem functioning experiments. Proc. R. Soc. B 287, 20202063 (2020).Article 
    CAS 

    Google Scholar 
    Cong, W.-F. et al. Plant species richness promotes soil carbon and nitrogen stocks in grasslands without legumes. J. Ecol. 102, 1163–1170 (2014).Article 
    CAS 

    Google Scholar 
    Leimer, S. et al. Mechanisms behind plant diversity effects on inorganic and organic N leaching from temperate grassland. Biogeochemistry 131, 339–353 (2016).Article 
    CAS 

    Google Scholar 
    Xu, Q. et al. Consistently positive effect of species diversity on ecosystem, but not population, temporal stability. Ecol. Lett. 24, 2256–2266 (2021).Article 

    Google Scholar 
    Hector, A. et al. General stabilizing effects of plant diversity on grassland productivity through population asynchrony and overyielding. Ecology 91, 2213–2220 (2010).Article 
    CAS 

    Google Scholar 
    Turnbull, L. A., Levine, J. M., Loreau, M. & Hector, A. Coexistence, niches and biodiversity effects on ecosystem functioning. Ecol. Lett. 16, 116–127 (2013).Article 

    Google Scholar 
    Wright, A. J. et al. Flooding disturbances increase resource availability and productivity but reduce stability in diverse plant communities. Nat. Commun. 6, 6092 (2015).Article 
    ADS 
    CAS 

    Google Scholar 
    Fischer, F. M. et al. Plant species richness and functional traits affect community stability after a flood event. Philos. Trans. R. Soc. B 371, 20150276 (2016).Article 

    Google Scholar 
    Roscher, C. et al. A functional trait-based approach to understand community assembly and diversity–productivity relationships over 7 years in experimental grasslands. Perspect. Plant Ecol. Evol. Syst. 15, 139–149 (2013).Article 

    Google Scholar 
    Eisenhauer, N. et al. Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Res. Ideas Outcomes 5, e47042 (2019).Article 

    Google Scholar 
    van Moorsel, S. J., Schmid, M. W., Hahl, T., Zuppinger-Dingley, D. & Schmid, B. Selection in response to community diversity alters plant performance and functional traits. Perspect. Plant Ecol. Evol. Syst. 33, 51–61 (2018).Article 

    Google Scholar 
    van Moorsel, S. J. et al. Community evolution increases plant productivity at low diversity. Ecol. Lett. 21, 128–137 (2018).Article 

    Google Scholar 
    Roeder, A. et al. Plant diversity effects on plant longevity and their relationships to population stability in experimental grasslands. J. Ecol. 109, 2566–2579 (2021).Article 

    Google Scholar 
    Cadotte, M. W., Dinnage, R. & Tilman, D. Phylogenetic diversity promotes ecosystem stability. Ecology 93, S223–S233 (2012).Article 

    Google Scholar 
    Pu, Z., Daya, P., Tan, J. & Jiang, L. Phylogenetic diversity stabilizes community biomass. J. Plant Ecol. 7, 176–187 (2014).Article 

    Google Scholar 
    Carrara, F., Giometto, A., Seymour, M., Rinaldo, A. & Altermatt, F. Experimental evidence for strong stabilizing forces at high functional diversity of aquatic microbial communities. Ecology 96, 1340–1350 (2015).Article 

    Google Scholar 
    Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a conceensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).Article 

    Google Scholar 
    Ruijven, J. V. & Berendse, F. Contrasting effects of diversity on the temporal stability of plant populations. Oikos 116, 1323–1330 (2007).Article 

    Google Scholar 
    Proulx, R. et al. Diversity promotes temporal stability across levels of ecosystem organization in experimental grasslands. PLoS ONE 5, e13382 (2010).Article 
    ADS 

    Google Scholar 
    Hoaglin, D. C., Iglewicz, B. & Tukey, J. W. Performance of some resistant rules for outlier labeling. JASA 81, 991–999 (1986).Article 
    MathSciNet 

    Google Scholar 
    Loreau, M. & de Mazancourt, C. Species synchrony and its drivers: neutral and nonneutral community dynamics in fluctuating environments. Am. Nat. 172, E48–E66 (2008).Article 

    Google Scholar 
    Gross, K. et al. Species richness and the temporal stability of biomass production: a new analysis of recent biodiversity experiments. Am. Nat. 183, 1–12 (2014).Article 

    Google Scholar 
    Schmid, B., Baruffol, M., Wang, Z. & Niklaus, P. A. A guide to analyzing biodiversity experiments. J. Plant Ecol. 10, 91–110 (2017).Article 

    Google Scholar 
    Rosseel, Y. lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).Article 

    Google Scholar  More

  • in

    Silent gene clusters encode magnetic organelle biosynthesis in a non-magnetotactic phototrophic bacterium

    The phototrophic species Rhodovastum atsumiense G2-11 acquired MGCs from an unknown alphaproteobacterial MTB by recent HGTIn a systematic database search for novel MGCs, we identified several orthologs of known magnetosome genes in the recently released draft genome sequence of the culturable anoxygenic phototroph Rhodovastum atsumiense G2-11 [25]. This finding was unexpected as, after isolation of G2-11 from a paddy field more than 20 years ago, no magnetosome formation has been reported [26]. Furthermore, no MTB has been identified so far among phototrophs or within the Acetobacteraceae family to which G2-11 belongs [26] (Fig. 1a).Fig. 1: Phylogeny, chromosome, and MGCs organization of G2-11.a The maximum likelihood phylogenetic tree based on ribosomal proteins demonstrates the position of G2-11 (highlighted in red) within family Acetobacteraceae (highlighted in the yellow box). The Azospirillaceae family was used as an outgroup based on the latest Alphaproteobacteria phylogeny. Branch length represents the number of base substitutions per site. Values at nodes indicate branch support calculated from 500 replicates using non-parametric bootstrap analysis. Bootstrap values 20 genes with no homology to known magnetosome genes (Fig. 1c). In contrast, the compact MGCs in G2-11 include only a few genes that could not be associated with magnetosome biosynthesis.Tetranucleotide usage patterns are frequently employed as a complementary tool to group organisms since they bear a reliable phylogenetic signal [32]. Likewise, deviations of tetranucleotide usage in a certain fragment from the flanking genome regions can indicate HGT [21]. Comparison of the z-normalized tetranucleotide frequencies of the MGCs (27.5 kb) with the flanking upstream (117.7 kb) and downstream (79.5 kb) fragments showed a considerably lower correlation between them (Pearson’s r = 0.88 with both flanking fragments) than between the flanking fragments themselves (Pearson’s r = 0.97, Fig. 1e). This indicates a significant difference in the tetranucleotide composition of the MGCs compared to the flanking genomic regions and supports a foreign origin of the magnetosome genes in G2-11 suggested by the phylogenetic analysis. Besides, the presence of a mobile element (transposase) and position of the MGCs directly downstream of a tRNA gene, a common hotspot for integration of genomic islands [33,34,35], suggests that the MGCs of G2-11 are indeed located on a genomic island, i.e., represent MAI, like in many other MTB [20, 21]. Unfortunately, the lack of other representatives of the genus Rhodovastum makes it impossible to infer whether the MAI was transferred directly to G2-11 or the last common ancestor of the genus. Nonetheless, its compact organization and conspicuous tetranucleotide usage suggest a relatively recent HGT event.G2-11 does not form magnetosomes under laboratory conditionsAlthough magnetosome genes discovered in G2-11 comply with the minimal set required for magnetosome biomineralization in MSR-1 [36], no magnetosomes have been detected in this organism. It might have several explanations: (i) the strain might switch to the magnetotactic lifestyle only under very specific, yet not tested, conditions; (ii) it once was able to synthesize magnetosomes in its natural environment but lost this ability upon subcultivation due to mutations before its characterization; (iii) the strain might naturally not exploit magnetotaxis as its genes might be non-functional or not actively expressed. To clarify which of these explanations is most likely, we first tested whether G2-11 can form magnetosomes under different laboratory conditions. To this end, the strain was cultivated photoheterotrophically, anoxic or microoxic, in a complex medium with potassium lactate and soybean peptone, as commonly used for MSR-1 (FSM) [37], as well as in minimal media with different C-sources previously shown to support growth in G2-11 (glucose, pyruvate, L-glutamine, and ethanol) [26]. All media were supplied with 50 μM ferric citrate to provide sufficient iron for magnetite biomineralization. Since magnetosome biosynthesis is possible only under low oxygen tension, aerobic chemoheterotrophic growth of G2-11 was not tested. The best growth was observed in the complex FSM medium and a minimal medium with glucose or pyruvate, whereas L-glutamine and ethanol supported only weak growth (Supplementary Fig. S3). Irrespective of the growth stage, none of the tested cultures demonstrated magnetic response as measured by a magnetically induced differential light scattering assay (Cmag) [38]. Consistently, micrographs of cells collected from stationary phase cultures did not show any magnetosome-like particles (Supplementary Fig. S3). This confirmed that G2-11 indeed cannot biosynthesize magnetosomes, at least under the conditions available for the laboratory tests. During cultivation, we also noticed that G2-11 cells did not move at any growth stage despite the initial description of this organism as motile using a single polar flagellum [26], and containing several flagellum synthesis operons and other motility-related genes. Moreover, the cells tended to adhere to glass surfaces under all tested conditions and formed a dense clumpy biofilm immersed in a thick extracellular matrix (Supplementary Fig. S3a-ii).Considering that G2-11 generally lacks magnetosomes and appears to have a stationary lifestyle, which is not consistent with magnetotaxis, we assessed whether the maintenance of MGCs comes at fitness costs for the organism. To this end, we deleted the entire region containing the magnetosome genes (in the following, referred to as the MAI region) using the genetic tools we established for G2-11 in this work (Supplementary Fig. S4a, see Materials and Methods for details). After PCR screening, replica plating test, and genome re-sequencing, two of G2-11 ΔMAI mutants were selected for further analysis (Supplementary Fig. S5). These mutants showed no significant differences in the growth behavior compared to the wildtype (WT) when incubated in minimal media supplied with acetate or pyruvate as a sole carbon source (Supplementary Fig. S4b). This finding suggests that the presence of the magnetosome genes neither provides benefits nor poses any substantial metabolic burden for G2-11, at least under the given experimental conditions.RNAseq reveals poor expression levels and antisense transcription in the MGCs of G2-11We set on to determine whether the magnetosome genes are transcribed in G2-11. To this end, we analyzed its whole transcriptome for the photoheterotrophic conditions, under which the best growth was observed, in two biological replicates. The expression levels of all the encoded genes calculated as TPM (transcripts per million) demonstrated a high correlation between the two replicates (Pearson’s r = 0.98). Most genes of the (mms6-like1)(mmsF-like1)mamH1IEKLMOH2 cluster were only poorly or not transcribed at all (Fig. 2a, Supplementary dataset). Transcription of mms6-like1, mamF-like1, mamL, mamH1, mamI, and mamK, for example, did not pass the noise background threshold (TPM ≤ 2) in both replicates and were unlikely to be expressed, whereas mamE, mamM, mamH2, feoAm, and feoBm slightly exceeded the threshold in at least one replicate and might be weakly transcribed (Fig. 2a). Although the TPM of mamO (TPM = 5.67–6.10, Supplementary dataset) exceeded the background threshold, the coverage plot reveals that the number of mapped reads sharply rises at its 3’-end, whereas the 5’-end has low read coverage (Fig. 2b). This indicates the presence of an internal transcription start site (TSS) and its associated promoter within the coding sequence of mamO instead of the full transcription of the gene. Localization of an active promoter within mamO was recently described in MSR-1, suggesting that the transcriptional organization of MGCs may be more broadly conserved across MTB than assumed previously [39].Fig. 2: Transcription of the magnetosome genes in G2-11.a Log10 of the transcript abundances for all genes in the G2-11 genome presented as TPM (transcripts per million). Red dots represent the magnetosome genes. Red rectangle shows genes with TPM below the threshold, and blue rectangle shows genes with expression levels above median. R1 and R2: biological replicates. Pearson’s r and the p value is presented on the graph. b RNAseq coverage of reads mapped on the positive (red) and negative (blue) strands of the genome in the MAI region. The gray balk shows the gene map: genes encoded on the negative strand are colored in black, on the positive – in green. Red arrows indicate the anti-sense transcription in the mamPAQRBST operon. Green arrows indicate the intragenic TSS within mamO. TSS are indicated with dashed lines and black arrowheads that show the direction of transcription.Full size imageTranscription of genes within the mag123, (mms6-like2)(mmsF-like2), and mamAPQRBST clusters significantly exceeded the threshold, with the expression levels of mag1, mamT, and mamS being above the overall median. At the same time, antisense transcription was detected in the mamAPQRBST region, with the coverage considerably exceeding the sense transcription (Fig. 2b). This antisense RNA (asRNA) likely originated from a promoter controlling the tRNA gene positioned on the negative strand downstream of mamT. Such long asRNAs have the potential to interfere with sense transcripts, thereby significantly decreasing the expression of genes encoded on the opposite strand [40].In summary, the RNAseq data revealed extremely low or lack of transcription of several genes that are known to be essential for magnetosome biosynthesis (mamL, mamI, mamM, mamE, and mamO) [27, 41]. Additionally, the detected antisense transcription can potentially attenuate expression of the mamAPQRBST cluster that also comprises essential genes, i.e., mamQ and mamB. Although other factors, like the absence of several accessory genes mentioned above and the potential accumulation of point mutations, might also be involved, the lack or insufficient transcription of the essential magnetosome genes appears to be the primary reason for the absence of magnetosome biosynthesis in G2-11.Magnetosome proteins from G2-11 are functional in a model magnetotactic bacteriumAlthough visual inspection of the G2-11 magnetosome genes did not reveal any frameshifts or other apparent mutations, accumulation of non-obvious functionally deleterious point substitutions in the essential genes could not be excluded. Therefore, we next tested whether at least some of the magnetosome genes from G2-11 still encode functional proteins that can complement isogenic mutants of the model magnetotactic bacterium MSR-1. In addition, we analyzed the intracellular localization of their products in both MSR-1 and G2-11 by fluorescent labeling.One of the key proteins for magnetosome biosynthesis in MSR-1 is MamB, as its deletion mutant is severely impaired in magnetosome vesicle formation and is entirely devoid of magnetite crystals [42, 43]. Here, we observed that expression of MamB[G2-11] partially restored magnetosome chain formation in MSR-1 ΔmamB (Fig. 3a, b-i, b-ii). Consistently, MamB[G2-11] tagged with mNeonGreen (MamB[G2-11]-mNG) was predominantly localized to magnetosome chains in MSR-1, suggesting that the magnetosome vesicle formation was likely restored to the WT levels (Fig. 3b-iii).Fig. 3: Genetic complementation and intracellular localization of magnetosome proteins from G2-11 in MSR-1 isogenic mutants.a TEM micrograph of MSR-1 wildtype (WT). b MSR-1 ΔmamB::mamB[G2-11]. b-i TEM micrograph and b-ii magnetosome chain close-up; b-iii) 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamB::mamB[G2-11]-mNG. c MSR-1ΔmamQ::mamQ[G2-11]. c-i TEM micrograph and c-ii close-up of the particles; c-iii 3D-SIM Z-stack maximum intensity projection. d MSR-1 ΔmamK::mamK[G2-11]. d-i TEM micrograph of MSR-1 ΔmamK; d-ii TEM micrograph of MSR-1 ΔmamK::mamK[G2-11]; d-iii 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamK::mNG-mamK[G2-11]. e MSR-1 ΔmamKY::mamK[G2-11]. e-i-ii Representative cells of MSR-1 ΔmamKY mutant showing examples of a short chain, cluster (e-i), and ring-shaped chain (e-ii); (e-iii) TEM micrograph of MSR ΔmamKY::mamK[G2-11] mutant showing the complemented phenotype; e-iv distribution of cells with different phenotypes in the populations of MSR-1 ΔmamKY and MSR-1 ΔmamKY::mamK[G2-11] mutants (N  > 50 cells for each strain population); e-v 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamKY::mNG-mamK[G2-11]. f MSR-1 ΔmamJ::mamJ-like[G2-11]. f-i TEM micrograph of MSR-1 ΔmamJ; f-ii TEM micrograph of MSR-1 ΔmamJ::mamJ-like[G2-11]; f-iii 3D-SIM Z-stack maximum intensity projection of MSR-1 ΔmamJ::mamJ-like[G2-11]-gfp. g MSR-1 ΔF3::mmsF-like1[G2-11] and ΔF3::mmsF-like2[G2-11]. g-i TEM micrograph of MSR-1 ΔF3; g-ii TEM micrograph of MSR-1 ΔF3::mmsF-like1[G2-11]; g-iii TEM micrograph of MSR-1 ΔF3::mmsF-like2[G2-11]; g-iv magnetosome diameter distribution in MSR-1 ΔF3 and the mutants complemented with mmsF-like1/mmsF-like2. Asterisks indicate points of significance calculated using Kruskal–Wallis test (****p 50 cells for each of two randomly selected insertion mutants MSR-1 ΔmamKY::mamK[G2-11] revealed that the long magnetosome chains were restored in 35-40% of the population (Fig. 3e-iv). Of note, mNG-MamK[G2-11] formed slightly shorter filaments in MSR-1 ΔmamKY than in ΔmamK, which were also characteristically displaced to the outer cell curvature due to the lack of mamY [46] (Fig. 3e-v).MamJ attaches magnetosomes to the MamK filament in MSR-1, mediating their chain-like arrangement. Elimination of mamJ disrupts this linkage, causing magnetosomes to aggregate owing to magnetic interactions [47] (Fig. 3f-i). In MSR-1, MamJ is encoded within the mamAB operon, between mamE and mamK. Within the (mms6-like1)(mmsF-like1)mamH1IEKLMOH2 cluster of G2-11, there is an open reading frame (ORF) encoding a hypothetical protein that is located in a syntenic locus (Fig. 1c). Although the hypothetical protein from G2-11 and MamJ from MSR-1 differ considerably in length (563 vs. 426 aa), share only a low overall sequence similarity (31%), and are not identified as orthologues by reciprocal blast analyses, multiple sequence alignments revealed a few conserved amino acids at their N- and C-termini (Supplementary Fig. S6). Moreover, in both proteins, these conserved residues are separated by a large region rich in acidic residues (pI 3.3 and 3.2) suggesting that the G2-11 protein might be a distant MamJ homolog. To test if it implements the same function as MamJ, we transferred this gene to MSR-1 ΔmamJ. Interestingly, it indeed restored chain-like magnetosome arrangement, which, however, often appeared as closed rings rather than linear chains (Fig. 3f-ii). Despite this difference, it indicated the ability of the hypothetical protein (hereafter referred to as MamJ-like[G2-11]) to attach magnetosomes to MamK, suggesting that in the native context, it can have a function identical to MamJ. Consistently, its fluorescently labeled version was often observed in ring-like structures within the cytoplasm of MSR-1 ΔmamJ, suggesting that it is indeed localized to magnetosomes (Fig. 3f-iii).In magnetospirilla, magnetosome proteins MmsF, MamF, and MmxF share an extensive similarity. Their individual and collective elimination gradually reduces the magnetite crystal size and disrupts the chain formation in MSR-1 (Fig. 3g-i; Paulus, manuscript in preparation). The MAI of G2-11 includes two genes, whose products have high similarity to these proteins, designated here as MmsF-like1[G2-11] and MmsF-like2[G2-11]. Expression of each of them in the MSR-1 ΔmmsFΔmamFΔmmxF triple mutant (ΔF3) partially restored the magnetosome size and led to the formation of short magnetosome chains in MSR ΔF3::mmsF-like1[G2-11] (Fig. 3g-ii) or clusters in MSR-1 ΔF3::mmsF-like2[G2-11] (Fig. 3g-iii, iv). Consistently, fluorescently tagged mNG-MmsF-like1[G2-11] and mNG-MmsF-like2[G2-11] localized to magnetosomes in the pattern resembling that in the TEM micrographs of the complemented corresponding mutants (Fig. 3g-v, vii), or were perfectly targeted to the magnetosome chains in MSR-1 WT (Fig. 3g-vi, viii).In G2-11, MamB[G2-11]-mNG, mNG-MamQ[G2-11], MamJ-like[G2-11]-GFP, mNG-MmsF-like1[G2-11], and mNG-MmsF-like2[G2-11] were patchy-like or evenly distributed in the inner and intracellular membranes (Supplementary Fig. S7). No linear structures that would indicate the formation of aligned magnetosome vesicles were observed in these mutants. As expected, mNG-MamK[G2-11] formed filaments in G2-11 (Supplementary Fig. S7c).Expression of MamM, MamO, MamE, and MamL failed to complement the corresponding deletion mutants of MSR-1 (not shown). Although detrimental mutations in the genes cannot be excluded, this result can be attributed to the lack of their native, cognate interaction partners, likely due to the large phylogenetic distances between the respective orthologues.Transfer of MGCs from MSR-1 endows G2-11 with magnetosome biosynthesis that is rapidly lost upon subcultivationHaving demonstrated the functionality of several G2-11 magnetosome genes in the MSR-1 background, we wondered whether, conversely, the G2-11 background is permissive for magnetosome biosynthesis. To this end, we transferred the well-studied MGCs from MSR-1 into G2-11, thereby mimicking an HGT event under laboratory conditions. The magnetosome genes from MSR-1 were previously cloned on a single vector pTpsMAG1 to enable the one-step transfer and random insertion into the genomes of foreign organisms [23]. Three G2-11 mutants with different positions of the integrated magnetosome cassette were incubated under anoxic phototrophic conditions with iron concentrations (50 μM) sufficient for biomineralization in the donor organism MSR-1. The obtained transgenic strains indeed demonstrated a detectable magnetic response (Cmag = 0.38 ± 0.11) [38], and TEM confirmed the presence of numerous electron-dense particles within the cells (Fig. 4), which, however, were significantly smaller than magnetosome crystals of MSR-1 (ranging 18.5 ± 4.3 nm to 19.9 ± 5.0 nm in three G2-11 MAG insertion mutants vs 35.4 ± 11.5 nm in MSR-1 WT, Fig. 4b) and formed only short chains or were scattered throughout the cells (Fig. 4a, c-i). Mapping of the particle elemental compositions with energy-dispersive X-ray spectroscopy (EDS) in STEM mode revealed iron- and oxygen-dominated compositions, suggesting they were iron oxides. High-resolution TEM (HRTEM) images and their FFT (Fast Fourier Transform) patterns were consistent with the structure of magnetite (Fig. 4c). Thus, G2-11 was capable of genuine magnetosome formation after acquisition of the MGCs from MSR-1.Fig. 4: Magnetosome biosynthesis by G2-11 upon transfer of the MGCs from MSR-1.a A cell with magnetosomes (i) and a close-up of the area with magnetosome chains (ii). Scale bars: 1 µm. b Violin plots displaying magnetosome diameter in three MAG insertion mutants of G2-11 in comparison to MSR-1. Asterisks indicate points of significance calculated using the Kruskal–Wallis test (**** designates p  More