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Figure 2. A in Guidelines and quantitative standards to improve consistency in cetacean subspecies and species delimitation relying on molecular genetic data

Figure 2. A comparison of the pairs of populations (red triangles), subspecies (green squares) and species (blue circles) estimated by Rosel et al. (2017a). Net nucleotide divergence (dA) is shown on a natural log scale to better illustrate differences between the pairwise comparisons at low levels of divergence. Bars show the central 95th-pecentile of the estimate distributions. The solid vertical line at dA = 0.020 delimits all but one species and correctly excludes all subspecies pairs. The vertical dashed line at dA = 0.004 delimits all populations from the higher taxonomic levels and correctly delimits seven of eleven subspecies. The horizontal dashed lines are two potential thresholds for percent diagnosable (80% and 95%) that are discussed in the text.

Figure 4 in Diagnosability of mtDNA with Random Forests: Using sequence data to delimit subspecies

Figure 4. GAM fit of number of migrants (Nem) from Model 2 parameters. Solid line shows median value of predicted percent correctly classified, and shaded area shows 95% CI. The switch from bimodal distribution to a normal distribution occurs at Nem = 1 (log10Nem = 0).

Figure 3 in Diagnosability of mtDNA with Random Forests: Using sequence data to delimit subspecies

Figure 3. Two-dimensional GAM fits of effective population size (Ne), divergence time in generations (T), and mutation rate (µ) from Model 1 simulated data. Results from models without migration to the left and those with migration to the right. Colors indicate model prediction of percent correctly classified.

Figure 1 in Diagnosability of mtDNA with Random Forests: Using sequence data to delimit subspecies

Figure 1. (A) Distribution of a hypothetical character for two putative subspecies (red and blue) demonstrating minimum overlap necessary to satisfy 75% rule of Amadon (1949). Character is continuous on the x-axis. Dashed lines indicate the point at which 75% of each distribution is outside of 99%+ of the other. Solid line indicates point of overlap where 97% of both distributions are outside one another. (B) Probability of membership to subspecies for specimens having values along the character axis. Probability is based on the ratio of the distribution frequencies at each point along the x-axis, with a 50:50 probability occurring at the threshold point.

opencc-zeroNov 2022View details →

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Standardized nuclear markers improve and homogenize species delimitation in Metazoa

Species are the fundamental units of life and evolution. Their recognition is essential for science and society. Molecular methods have been increasingly employed for the identification of animal species, despite several challenges. Here, we explore with genomic data from nine animal lineages a set of nuclear markers, namely metazoan-level universal single-copy orthologs (metazoan USCOs), for their use in species delimitation. Our data sets include arthropods and vertebrates. We use various data assembly strategies and employ coalescent-based species inference as well as population admixture analyses and phenetic methods. We demonstrate that metazoan USCOs well distinguish closely related morphospecies and consistently outperform classical mitochondrial DNA barcoding in discriminating closely related species in different animal taxa. USCOs overcome the general shortcomings of mitochondrial DNA barcodes, and due to standardization across Metazoa, also those of other approaches. They accurately assign samples not only to lower but also to higher taxonomic levels. Metazoan USCOs provide a powerful and unifying framework for DNA-based species delimitation and taxonomy in animals and their employment could result in a more efficient use of research data and resources.

opencc-by-4.0Aug 2022View details →

Database of Rural Technological Trajectories of the Legal Amazon delimited by the Method of Differentiation and Structural Signification of Rural Production

This database contains selected variables associated with the rural economic sector of the Brazilian Legal Amazon distributed at municipal level by technological trajectories (TT) – techno-productive trajectories and their technological variants (TTP) -, as defined and theoretically justified by Costa (2021, p. 217-219). The TTs are designed by a method that combines differentiation and structural signification of rural production in a given territory – hereafter, Method of Differentiation and Structural Signification of Rural Production (M-DESTRU). Structural differentiation (Phase 1) is necessary because production systems activities play different roles, depending on the systems  production modes and their territorial context: cattle ranching, for example, performs very different economic functions when practiced in family structures (peasants) in the municipalities of the Lower Amazonas, in comparison with wage-based farms in Southeast Pará; the roles played by temporary crops in the peasant systems of the Lower Tocantins are also quite different from those that are observed among employers' establishments in the Lower Amazon; and so on. This phase of the methodology qualifies these differences and has its procedures described on pages 441 and 442 of Costa (2021). In phase 2, M-DESTRU verifies how these structurally dissimilar activities, combine with others linked to the practices of the agents of each production mode, conforming convergences that result in distinct patterns. These patterns are semantically associated with TTs or TTPs structures that are in movement, and these structures all together make up for the region's rural economic system. This Phase's procedures are detailed on pages 441 and 442 of the aforementioned work. The territory of the Brazilian Legal Amazon encompasses 772 municipalities: all from eight states (Acre, Amapá, Amazonas, Mato Grosso, Pará, Rondônia, Roraima and Tocantins) and part of the State of Maranhão (west of the 44ºW meridian). The base data are from the Brazilian Institute of Geography and Statistics (IBGE), from the 1995, 2006 and 2017 Agricultural Censuses. The credit data for 2017 are from the Central Bank of Brazil. The dataset is organized as: Zen1995_LegalAmazon_Inicial.csv; Zen2006_LegalAmazon_Inicial.csv and Zen2017_LegalAmazon_Inicial.csv. In each table the column names are self-explanatory.   Reference: <ul> <li>Costa FA. 2021. Structural diversity and change in rural Amazonia: A comparative assessment of the technological trajectories based on agricultural censuses (1995, 2006 and 2017). Nova Economia 31(2).       </li> </ul>

Fig. 5 in Species delimitation in the genus Ochraethes Chevrolat, 1860 (Coleoptera: Cerambycidae), with description of two new species

Fig. 5. Species delimitation in Ochraethes Chevrolat, 1860. Maximum likelihood tree inferred from COI in IQ TREE. The molecular operational taxonomic units (MOTU) are separated by colour bars. Abbreviations: ABGD = ast recursive analyses; bPTP = both Maximum likelihood and Bayesian analyses; GMYC = coalescence and yule analyses; MORP = morphology.

Fig. 3 in Species delimitation in the genus Ochraethes Chevrolat, 1860 (Coleoptera: Cerambycidae), with description of two new species

Fig. 3. Pubescence variation on the elytra in Ochraethes Chevrolat, 1860. A–B. Ochraethes brevicornis (Chevrolat, 1860) (♀, ♂). C–E. O. cinereolus (Bates, 1892) comb. nov. (♂, ♂, ♀). F–I. O. obliquus (Chevrolat, 1860) (♂, ♂, ♀, ♀). J–N. O. sommeri (Chevrolat, 1835) (♂, ♂, ♂, ♀, ♀). O–S. O. viridiventris (Chevrolat, 1860) (♂, ♀, ♂, ♂, ♀). T–X. O. z-littera (Chevrolat, 1860) (♂, ♂, ♂, ♀, ♀).

Fig. 2 in Species delimitation in the genus Ochraethes Chevrolat, 1860 (Coleoptera: Cerambycidae), with description of two new species

Fig. 2. Ochraethes nigroapicalis sp. nov. A–D. Holotype, ♂ (EMEC). A. Habitus, dorsal. B. Habitus, ventral. C. Habitus, lateral. D. Frons. E. Paratype, ♂ (CNIN), ventral view of male genitalia. F. Paratype, ♀ (EMEC), habitus, dorsal.

Fig. 4 in Species delimitation in the genus Ochraethes Chevrolat, 1860 (Coleoptera: Cerambycidae), with description of two new species

Fig. 4. Head, frontal view of type species of Ochraethes. A. Ochraethes brevicornis (Chevrolat, 1860), ♀. B. O. virescens (Chevrolat, 1860), ♂. C. O. cinereolus (Bates, 1892) comb. nov., ♀. D. O. octomaculata Chemsak & Noguera, 2001, ♂. E. O. obliquus (Chevrolat, 1860), ♂. F. O. zebratus Bates, 1885, ♀. G. O. sommeri (Chevrolat, 1835), ♂. H. O. circuliferus (Chevrolat, 1860) (= Ochraethes sommeri), ♀. I. Trichoxys giesberti Botero et al., 2019, ♀. J. O. viridiventris (Chevrolat, 1860), ♂. K. O. nigritus Bates, 1892 (= Ochraethes viridiventris), ♂. L. O. clerinus Bates, 1892, ♀. M. O. z-littera (Chevrolat, 1860), ♂. N. O. cristoforii (Chevrolat, 1860), ♂. O. O. litura Bates, 1885, ♀.

Fig. 1 in Species delimitation in the genus Ochraethes Chevrolat, 1860 (Coleoptera: Cerambycidae), with description of two new species

Fig. 1. Ochraethes confusus sp. nov. A–D. Holotype, ♂ (EMEC). A. Habitus, dorsal. B. Habitus, ventral. C. Habitus, lateral. D. Frons. E. Paratype, ♂ (CNIN), ventral view of male genitalia. F. Paratype, ♀ (EMEC), habitus, dorsal.

FIGURE 4 in Species delimitation reveals an underestimated diversity of Andean catfishes of the family Astroblepidae (Teleostei: Siluriformes)

FIGURE 4 | Species tree inferred from the concatenated dataset of mitochondrial genes (COI, Cytb, and 16S). Nodal support values are Bayesian posterior probabilities. Non-significant speciation probabilities identified in BP&P analysis algorithm A10 (PP:<0.95) are indicate by black circles and species supported with asterisk.

FIGURE 2 in Species delimitation reveals an underestimated diversity of Andean catfishes of the family Astroblepidae (Teleostei: Siluriformes)

FIGURE 2 | Map of northwestern South America showing the geographic distribution of samples used in this study and species distribution of Astroblepus reported in Global Biodiversity Information Facility (GBIF) and the California Academy of Sciences (CAS) databases.

FIGURE 1 in Species delimitation reveals an underestimated diversity of Andean catfishes of the family Astroblepidae (Teleostei: Siluriformes)

FIGURE 1 | Species of Astroblepus included in this study, A. A. ardiladuartei (LBP 26696 topotype live, 4.54 mm SL), B. A. cachara (LBP 26712 topotype live, 4.23 mm SL), C. A. caquetae (CZUT-IC 18464 topotype of museum, 7.84 mm SL), D. A. curitiensis (LBP 97118 topotype live, 5.92 mm SL), E. A. homodon (CZUT-IC 18390, 6.15 mm SL), F. A. gr. grixalvii (LBP24242 topotype live, 11.70 mm SL); F'. A. gr. grixalvii (CZUT-IC 18498 specimen of Magdalena basin 6,01 mm SL); F". A. gr. grixalvii (CZUT-IC 18320 specimen of Cauca basin, 15.25 mm SL), G. A. itae (topotype live, 3.58 mm SL), H. A. latidens (topotype live, 13.40 mm SL), I. A. onzagaensis (topotype live, 7.82 mm SL), J. A. pradai (topotype live, 4.53 mm SL), K. A. trifasciatus (topotype of museum, 9.65 mm SL), K'. A. trifasciatus (topotype of museum, 9.01 mm SL), L. A. aff. trifasciatus (specimen of Magdalena basin, 7.94 mm SL), M. A. verai (topotype live, 3.51 mm SL).

FIGURE 3 in Species delimitation reveals an underestimated diversity of Andean catfishes of the family Astroblepidae (Teleostei: Siluriformes)

FIGURE 3 | Results of single-locus approaches using cytochrome oxidase c subunit I (COI) for developing preliminary species delimitation hypothesis with 42 lineages. Results are represented on the ultrametric gene tree with collapsed nodes. All nodal support values were PP>0.95. Blocks at right of the tree represent hypothesized species groups and the values in the middle indicate the number of clusters identified by ABGD, bPTP and GMYC analyses for every collapsed node. COL: Colombia, ECU: Ecuador, PER: Peru.

Fig 9 in Species delimitation in the Stenocereus griseus (Cactaceae) species complex reveals a new species, S. huastecorum

Fig 9. Ripe fruit of S. huastecorum. Falling areolas (A, upper) and longitudinal cut (A, lower), aspect of a reproductive branch with immature fruits (B), and focus stacking micrograph (4X) of a seed hilum-micropylar region (C) and lateral view(D). Credits: (A, B) H. Alvarado-Sizzo (C) A. González-Murillo & H. Alvarado-Sizzo. Scale bars (A) = 1 cm; (C, D) = 1 mm. https://doi.org/10.1371/journal.pone.0190385.g009

Fig 8. A newly opened S in Species delimitation in the Stenocereus griseus (Cactaceae) species complex reveals a new species, S. huastecorum

Fig 8. A newly opened S. huastecorum flower. Lateral (A) and top (B) view, (C) longitudinal cut of the floral tube. (H. Alvarado-Sizzo 350). Credits: H. AlvaradoSizzo. Scale bars = 1 cm. https://doi.org/10.1371/journal.pone.0190385.g008

Fig 3 in Species delimitation in the Stenocereus griseus (Cactaceae) species complex reveals a new species, S. huastecorum

Fig 3. Genetic clustering summary. Color gradients represent BC belonging probability starting from the 75% threshold value, purple bars with green types bootstrap values are the three genetic barriers detected by Barrier, at the left the UPGMA dendrogram following the color code used in the BC. https://doi.org/10.1371/journal.pone.0190385.g003

Fig 6. Areolar morphometrics t in Species delimitation in the Stenocereus griseus (Cactaceae) species complex reveals a new species, S. huastecorum

Fig 6. Areolar morphometrics t-tests. (A-D) areolar features lengths comparisons, (E-F) spines counts comparisons. Levels not connected by the same letter are significantly different. https://doi.org/10.1371/journal.pone.0190385.g006

Fig 5 in Species delimitation in the Stenocereus griseus (Cactaceae) species complex reveals a new species, S. huastecorum

Fig 5. Niche suitability pairwise comparisons based on t-tests. Different letters represent levels of significant differences. https://doi.org/10.1371/journal.pone.0190385.g005