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Figure 3 from: Datry T, Allen D, Argelich R, Barquin J, Bonada N, Boulton A, Branger F, Cai Y, Cañedo-Argüelles M, Cid N, Csabai Z, Dallimer M, de Araújo JC, Declerck S, Dekker T, Döll P, Encalada A, Forcellini M, Foulquier A, Heino J, Jabot F, Keszler P, Kopperoinen L, Kralisch S, Künne A, Lamouroux N, Lauvernet C, Lehtoranta V, Loskotová B, Marcé R, Martin Ortega J, Matauschek C, Miliša M, Mogyorósi S, Moya N, Müller Schmied H, Munné A, Munoz F, Mykrä H, Pal I, Paloniemi R, Pařil P, Pengal P, Pernecker B, Polášek M, Rezende C, Sabater S, Sarremejane R, Schmidt G, Senerpont Domis L, Singer G, Suárez E, Talluto M, Teurlincx S, Trautmann T, Truchy A, Tyllianakis E, Väisänen S, Varumo L, Vidal J-P, Vilmi A, Vinyoles D (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes 7: e77750. https://doi.org/10.3897/rio.7.e77750

Figure 3 The DRYvER three-step workflow embedded within 7 Work Packages (WP) and the four main attributes of the DRYvER consortium (red ovals).

Figure 2 from: Datry T, Allen D, Argelich R, Barquin J, Bonada N, Boulton A, Branger F, Cai Y, Cañedo-Argüelles M, Cid N, Csabai Z, Dallimer M, de Araújo JC, Declerck S, Dekker T, Döll P, Encalada A, Forcellini M, Foulquier A, Heino J, Jabot F, Keszler P, Kopperoinen L, Kralisch S, Künne A, Lamouroux N, Lauvernet C, Lehtoranta V, Loskotová B, Marcé R, Martin Ortega J, Matauschek C, Miliša M, Mogyorósi S, Moya N, Müller Schmied H, Munné A, Munoz F, Mykrä H, Pal I, Paloniemi R, Pařil P, Pengal P, Pernecker B, Polášek M, Rezende C, Sabater S, Sarremejane R, Schmidt G, Senerpont Domis L, Singer G, Suárez E, Talluto M, Teurlincx S, Trautmann T, Truchy A, Tyllianakis E, Väisänen S, Varumo L, Vidal J-P, Vilmi A, Vinyoles D (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes 7: e77750. https://doi.org/10.3897/rio.7.e77750

Figure 2 It shows how DRYvER will use this cyclic model as a structured loop embedded in a meta-system perspective to guide adaptive management of DRNs. DRYvER will translate climate projections into changes in flow intermittence patterns at multiple scales, including that of the strategically-selected focal DRNs. This physical setting will then be used to implement a dynamic meta-system perspective to understand the cascading changes in biodiversity, ecosystem functions and ecosystem services. This knowledge will be integrated to develop a multi-criteria decision framework combining scientific, management, socio-economic, legislative barriers and leverages to promote an adaptive management of DRNs.

Figure 4 from: Datry T, Allen D, Argelich R, Barquin J, Bonada N, Boulton A, Branger F, Cai Y, Cañedo-Argüelles M, Cid N, Csabai Z, Dallimer M, de Araújo JC, Declerck S, Dekker T, Döll P, Encalada A, Forcellini M, Foulquier A, Heino J, Jabot F, Keszler P, Kopperoinen L, Kralisch S, Künne A, Lamouroux N, Lauvernet C, Lehtoranta V, Loskotová B, Marcé R, Martin Ortega J, Matauschek C, Miliša M, Mogyorósi S, Moya N, Müller Schmied H, Munné A, Munoz F, Mykrä H, Pal I, Paloniemi R, Pařil P, Pengal P, Pernecker B, Polášek M, Rezende C, Sabater S, Sarremejane R, Schmidt G, Senerpont Domis L, Singer G, Suárez E, Talluto M, Teurlincx S, Trautmann T, Truchy A, Tyllianakis E, Väisänen S, Varumo L, Vidal J-P, Vilmi A, Vinyoles D (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes 7: e77750. https://doi.org/10.3897/rio.7.e77750

Figure 4 DRYvER focal DRNs located in highly contrasted EU and CELAC biogeographic and climatic settings (red points), chosen to span the expected natural variability of drying processes and associated DRN responses.Mediterranean ecoregion: the Genal network, in Andalucía (Spain, Mediterranean climate), a dry region heavily impacted by climate change, where most rivers are already affected by drying (contact partner: UB);Alpine ecoregion: the Albarine network, in the Southern Jura (France, temperate climate), a region mildly impacted by climate change (the Albarine network is part of a national LTER project and monitored since 2006) (contact partner: INRAE);Continental ecoregion: the Velička network, in Morava (Czech Republic, continental climate), a region heavily impacted by climate change where many perennial rivers are shifting towards intermittent flow (contact partner: MU);Balkanic ecoregion: the Krka network, in the Dinaric Karst (Croatia, Mediterranean climate), a region where most rivers are already drying and heavily impacted by climate change (contact partner: UZ);Pannonian ecoregion: the Bükkösdi-víz network, in the Mecsek (Hungary, continental climate), a region moderately impacted by climate change, where DRNs are becoming common (contact partner: UP);Boreal ecoregion: the Vantaanjoki network, Helsinki-Uusimaa Region (Finland, boreal climate), region moderately impacted by climate change, where flow intermittence is currently rare (contact partner: SYKE);Pacific Lowlands: the Cube network, in the Andean-Choco region (Ecuador, tropical climate), a region where drying is very seasonal and increasing in duration and frequency (contact partner: USFQ);Central High Andes ecoregion: the Rio Chico network in the Sucre region (Bolivia, semi-arid climate), a dry area prone to desertification where political conflicts emerge due to water scarcity (contact partner: USFX);Caatinga ecoregion: the Jaguaribe network, in the Northeast Semiarid region (Brazil, semi-arid climate), the driest region in Brazil, already heavily impacted by climate change (contact partner: UFC).

Figure 1 from: Datry T, Allen D, Argelich R, Barquin J, Bonada N, Boulton A, Branger F, Cai Y, Cañedo-Argüelles M, Cid N, Csabai Z, Dallimer M, de Araújo JC, Declerck S, Dekker T, Döll P, Encalada A, Forcellini M, Foulquier A, Heino J, Jabot F, Keszler P, Kopperoinen L, Kralisch S, Künne A, Lamouroux N, Lauvernet C, Lehtoranta V, Loskotová B, Marcé R, Martin Ortega J, Matauschek C, Miliša M, Mogyorósi S, Moya N, Müller Schmied H, Munné A, Munoz F, Mykrä H, Pal I, Paloniemi R, Pařil P, Pengal P, Pernecker B, Polášek M, Rezende C, Sabater S, Sarremejane R, Schmidt G, Senerpont Domis L, Singer G, Suárez E, Talluto M, Teurlincx S, Trautmann T, Truchy A, Tyllianakis E, Väisänen S, Varumo L, Vidal J-P, Vilmi A, Vinyoles D (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes 7: e77750. https://doi.org/10.3897/rio.7.e77750

Figure 1 Phases of flowing and drying alternate annually in the naturally intermittent Albarine River (France), a focal DRN of DRYvER. About half of EU's river channels now flow intermittently and this fraction is increasing. Photos: T. Datry.

Figure 1 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 1 A Eighteen sampling localities of the genus the Trichiurus along the Chinese coast and the species composition after our surveys. Refer to Suppl. material 1: Table S1 for the abbreviations of localities. B The maximum-likelihood (ML) tree of these four Trichiurus species along the coast based on the COI gene. The numbers at the nodes are bootstrap values of the ML and NJ (neighbor-joining) analyses. The sampling size (n) indicated in parentheses C The photographs of four Trichiurus species used in the mitogenomes analyses.

Figure 3 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 3 The maximum-likelihood (ML) tree of the Trichiuridae based on the sequences of mitogenome (excluding d-loop). The numbers at the nodes are bootstrap values of the ML and NJ (neighbor-joining) analyses.

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Supplementary material 1 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Table S1–S4, Figure S1, S2

Figure 5 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 5 The simple regression and the boxplot analysis in T. japonicus (blue), T. lepturus (orange) and T. nanhaiensis (grey) A Total length [D(i,n)] and Preanal length [D(i,m)] B Caudal length [D(m,n)] and Body depth at anus [D(e,f)] C Head depth [D(d,o)] and Orbital length [D(j,k)] and D Head length [D(i,l)] and Head depth [D(d,o)]. The landmarks are illustrated in Fig. 2.

Figure 4 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 4 The maximum-likelihood (ML) tree of six Trichiurus species in the world based on the COI gene. The numbers at the nodes are bootstrap values of the ML and NJ (neighbor-joining) analyses.

Figure 9 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 9 Frequencies of different amino acids in the mitogenomes of the five Trichiurus species; the stop codon is not included.

Figure 10 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 10 . The mean partwise interspecific (gray) and intergeneric (black) p-distance in each gene.

Figure 8 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 8 Relative synonymous codon usage (RSCU) of the mitogenomes of the five Trichiurus species; the stop codon is not included. T. japonicus (TJ), T. lepturus (TL), T. nanhaiensis (TN), T. gangeticus (TG) and T. brevis (TB).

Figure 7 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 7 A Mean evolutionary rates for each protein coding gene in mitogenomes of five Trichiurus species B Evolutionary rates of ND6 gene of five Trichiurus species. C Evolutionary rates of Ka/Ks in ATP8 gene of five Trichiurus species. Indicated the rates of non-synonymous substitutions to the rate of synonymous substitutions (ka/ks). T. japonicus (TJ), T. lepturus (TL), T. nanhaiensis (TN), T. gangeticus (TG) and T. brevis (TB).

Figure 2 from: Yi M-R, Hsu K-C, Gu S, He X-B, Luo Z-S, Lin H-D, Yan Y-R (2022) Complete mitogenomes of four Trichiurus species: A taxonomic review of the T. lepturus species complex. ZooKeys 1084: 1-26. https://doi.org/10.3897/zookeys.1084.71576

Figure 2 Positions of 14 (a–n) landmarks used to contrast the morphological differences between Trichiurus species.

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Supplementary material 1 from: Odorico D, Nicosia E, Datizua C, Langa C, Raiva R, Souane J, Nhalungo S, Banze A, Caetano B, Nhauando V, Ragú H, Machunguene Jr M, Caminho J, Mutemba L, Matusse E, Osborne J, Wursten B, Burrows J, Cianciullo S, Malatesta L, Attorre F (2022) An updated checklist of Mozambique's vascular plants. PhytoKeys 189: 61-80. https://doi.org/10.3897/phytokeys.189.75321

The updated checklist of Mozambique's vascular plants

Figure 6 from: Odorico D, Nicosia E, Datizua C, Langa C, Raiva R, Souane J, Nhalungo S, Banze A, Caetano B, Nhauando V, Ragú H, Machunguene Jr M, Caminho J, Mutemba L, Matusse E, Osborne J, Wursten B, Burrows J, Cianciullo S, Malatesta L, Attorre F (2022) An updated checklist of Mozambique's vascular plants. PhytoKeys 189: 61-80. https://doi.org/10.3897/phytokeys.189.75321

Figure 6 Extinction risk of Mozambique's vascular plants. A assessed taxa B IUCN category for the evaluated taxa.

Figure 3 from: Odorico D, Nicosia E, Datizua C, Langa C, Raiva R, Souane J, Nhalungo S, Banze A, Caetano B, Nhauando V, Ragú H, Machunguene Jr M, Caminho J, Mutemba L, Matusse E, Osborne J, Wursten B, Burrows J, Cianciullo S, Malatesta L, Attorre F (2022) An updated checklist of Mozambique's vascular plants. PhytoKeys 189: 61-80. https://doi.org/10.3897/phytokeys.189.75321

Figure 3 Floristic patterns for Mozambique's vascular plants. A frequency of plant groups B geographic origin of taxa.

Figure 4 from: Abarenkov K, Kristiansson E, Ryberg M, Nogal-Prata S, Gómez-Martínez D, Stüer-Patowsky K, Jansson T, Põlme S, Ghobad-Nejhad M, Corcoll N, Scharn R, Sánchez-García M, Khomich M, Wurzbacher C, Nilsson RH (2022) The curse of the uncultured fungus. MycoKeys 86: 177-194. https://doi.org/10.3897/mycokeys.86.76053

Figure 4 The proportion of false-negative sequences (had reasonable matches; green) and false-negative sequences (had close matches; blue) out of all kingdom-level sequences over time (2001-2020). The figure suggests that the act of taking sequence annotation very lightly is not in an abating trend. The data for 2020 extend through early November 2020 and are thus partial.

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Supplementary material 1 from: Abarenkov K, Kristiansson E, Ryberg M, Nogal-Prata S, Gómez-Martínez D, Stüer-Patowsky K, Jansson T, Põlme S, Ghobad-Nejhad M, Corcoll N, Scharn R, Sánchez-García M, Khomich M, Wurzbacher C, Nilsson RH (2022) The curse of the uncultured fungus. MycoKeys 86: 177-194. https://doi.org/10.3897/mycokeys.86.76053

A list of the 29 journals under the Web of Science heading "Mycology" as of November 2020

Figure 2 from: Abarenkov K, Kristiansson E, Ryberg M, Nogal-Prata S, Gómez-Martínez D, Stüer-Patowsky K, Jansson T, Põlme S, Ghobad-Nejhad M, Corcoll N, Scharn R, Sánchez-García M, Khomich M, Wurzbacher C, Nilsson RH (2022) The curse of the uncultured fungus. MycoKeys 86: 177-194. https://doi.org/10.3897/mycokeys.86.76053

Figure 2 Pie chart representing all the 95,055 kingdom-level ITS sequences and the proportion of these that were true-positives (had no or only very distant taxonomically more well-annotated BLAST matches at the time of sequence deposition/release; red, 10%), false-negatives (had only reasonable matches; green, 17%) and false-negatives (had close matches; blue, 73%). The chart suggests that nearly all kingdom-level fungal ITS sequences in INSDC could have been given a more taxonomically-resolved name at the time of sequence deposition/release.