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Figure 2. The 49 in Phylogenetic structure among pocket gopher populations, genus Thomomys (Rodentia: Geomyidae), on the Baja California Peninsula

Figure 2. The 49 geographic locations where the samples were sequenced (letter). See Table 1 for the name of the localities. The lines indicate the hypothesized vicariance events that affected the Baja California Peninsula (BCP) fauna.

Figure 6 in Phylogenetic structure among pocket gopher populations, genus Thomomys (Rodentia: Geomyidae), on the Baja California Peninsula

Figure 6. Proposed subspecies distribution of Thomomys nigricans based on phylogenetic relationships, demographic history, and divergence times.

Figure 1 in Phylogenetic structure among pocket gopher populations, genus Thomomys (Rodentia: Geomyidae), on the Baja California Peninsula

Figure 1. Currently recognized subspecies of Thomomys anitae on the Baja California Peninsula (BCP). Type localities of each subspecies are: (1) 1.6 km east of El Rosario; (2) W side of the Colorado River, at old Hanlon Ranch, near Pilot Knob, Imperial Co., California; (3) Sierra Laguna, 2134 m a.s.l., Lower California; (4) Santa Anita, Lower California; (5) San[to] Tomás Baja California; (6) San Borjas Mission; (7) San Fernando Mission; (8) Punta Prieta; (9) Cataviña; (10) Los Palmitos, (western end Pattie Basin), on southeastern basin of Sierra Juarez (desert slope); (11) 1.6 km east of Rancho Lagunitas; (12) La Paz, Southern Lower California; (13) San Jorge, near Pacific coast west of Poza Grande and about 40.2 km south-west of Comondú, southern Lower California (altitude 15.2 m a.s.l.); (14) Sangre de Cristo; (15) Laguna Hanson, Sierra de Juárez; (16) Stearns Point, Magdalena Bay (west side), Lower California; (17) Las Palmas Canyon, 61 m a.s.l., western side of Laguna Salada; (18) Magdalena Island, Lower California; (19) San Pedro Martir mountains, Lower California, 213–2499.3 m a.s.l.; (20) Witch Creek, 11.2 km west of Julian, San Diego Co., 839.1 m a.s.l., California; (21) Boca La Playa, mesa bordering the sea, 25.7 km west of Santo Tomás; (22) Las Flores, 11.2 km south Bahía de Los Angeles; (23) 6.4 km north of Santa Catarina; (24) San Angel, 48.2 km west of San Ignacio, Lower California; (25) El Cajón, Canyon, 975.3 eastern base of Sierra San Pedro Martir, Baja California; (26) Balboa Park, San Diego California; (27) Near Diablito Spring, summit of San Matías Pass between Sierra Juarez and Sierra San Pedro Mártir, Baja California.

Figure 5 in Phylogenetic structure among pocket gopher populations, genus Thomomys (Rodentia: Geomyidae), on the Baja California Peninsula

Figure 5. Population expansion of Thomomys on the Baja California Peninsula (BCP). A, haplotype network of 119 haplotypes based on a fragment of cyt b (499 bp). The network shows three main clades that are also found by phylogenetic analyses. Each dot across the line between haplotypes represents a single base substitution. Dashed lines indicate the genetic break and the mutational steps between ancestral haplotypes. The numbers in the boxes indicate one of 119 unique haplotypes (Table 1); subscript numbers indicate the number of times the haplotype was sampled. B, mismatch distributions, based on the frequency of pairwise differences between all haplotypes. The grey line represents the expected Poisson distribution assuming a stepwise population expansion. The observed distribution is indicated by the black line.

opencc-zeroDec 2020View details →

Genetic diversity and population structure of two endangered neotropical parrots inform In Situ and Ex Situ conservation strategies

A key aspect in the conservation of endangered populations is understanding patterns of genetic variation and structure, which can provide managers with critical information to support evidence-based status assessments and management strategies. This is especially important for species with small wild and larger captive populations, as found in many endangered parrots. We used genotypic data to assess genetic variation and structure in wild and captive populations of two endangered parrots, the blue-throated macaw, Ara glaucogularis, of Bolivia, and the thick-billed parrot, Rhynchopsitta pachyrhyncha, of Mexico. In the blue-throated macaw, we found evidence of weak genetic differentiation between wild northern and southern subpopulations, and between wild and captive populations. In the thick-billed parrot we found no signal of differentiation between the Madera and Tutuaca breeding colonies or between wild and captive populations. Similar levels of genetic diversity were detected in the wild and captive populations of both species, with private alleles detected in captivity in both, and in the wild in the thick-billed parrot. We found genetic signatures of a bottleneck in the northern blue-throated macaw subpopulation, but no such signal was identified in any other subpopulation of either species. Our results suggest both species could potentially benefit from reintroduction of genetic variation found in captivity, and emphasize the need for genetic management of captive populations.

opencc-zeroAug 2021View details →

Nonrandom missing data can bias PCA inference of population genetic structure

Population genetic studies in non-model systems increasingly use next-generation sequencing to obtain more loci, but such methods also generate more missing data that may affect downstream analyses. Here we focus on the Principal Component Analysis (PCA) which has been widely used to explore and visualize population structure with mean-imputed missing data. We simulated data of different population models with various total missingness (1%, 10%, 20%) introduced either randomly or biased among individuals or populations. We found that individuals biased with missing data would be dragged away from their real population clusters to the origin of PCA plots, making them indistinguishable from true admixed individuals and potentially leading to misinterpreted population structure. We also generated empirical data of the big brown bat (Eptesicus fuscus) using restriction site-associated DNA sequencing (RADseq). We filtered three data sets with 19.12%, 9.87%, and 1.35% total missingness, all showing nonrandom missing data with biased individuals dragged towards the PCA origin, consistent with results from simulations. We highlight the importance of considering missing data effects on PCA in non-model systems where nonrandom missing data are common due to varying sample quality. To help detect missing data effects, we suggest to 1) plot PCA with a color gradient showing per sample missingness, 2) interpret samples close to the PCA origin with extra caution, 3) explore filtering parameters with and without the missingness-biased samples, and 4) use complementary analyses (e.g., model-based methods) to cross-validate PCA results and help interpret population structure.

Figure 4. The largetooth sawfish Pristis pristis. A in Species delineation and global population structure of Critically Endangered sawfishes (Pristidae)

Figure 4. The largetooth sawfish Pristis pristis. A, dorsal view of specimen from north-western Australia (photo: W. White); B, line drawing from FAO Species Catalogues.

Figure 1. Measurements adopted for Pristidae. A in Species delineation and global population structure of Critically Endangered sawfishes (Pristidae)

Figure 1. Measurements adopted for Pristidae. A, dorsal view: (1) total length; distance from rostrum tip to (2) eye, (3) spiracle, (4) pectoral fin insertion, (5) pelvic fin insertion, (6) first dorsal fin origin, (7) second dorsal fin origin, and (8) upper caudal fin origin; distance between bases, (15) interdorsal; distance between inner corners, (19) eyes, (20) spiracles, (106) eye length, and (107) spiracle length; rostrum measurements, (54) total length, (55) standard length, (57) rostrum width anterior, (61) rostrum width posterior, (62) interlateral rostral tooth anterior, and (67) interlateral rostral tooth posterior. B, ventral view, distance from rostrum tip to: (9) outer nostril, (10) mouth, (11) first gill, (12) third gill, and (13) posterior cloaca; distance between inner corners, (21) nostrils; pectoral fin lengths, (33) anterior margin, (34) posterior margin, (35) inner margin, and (36) base; other measurements, (28) mouth width, (30) nostril length, (32) clasper outer length. C, lateral view, first dorsal fin lengths: (41) anterior margin, (42) posterior margin, (43) height, (44) inner margin, and (45) base; second dorsal fin lengths: (46) anterior margin, (47) posterior margin, (48) height, (49) inner margin, and (50) base; caudal fin lengths, (51) upper lobe, (52) posterior margin, and (53) lower lobe. Drawings from Food and Agricultural Organization of the United Nations (FAO) Species Catalogues.

Figure 3 in Species delineation and global population structure of Critically Endangered sawfishes (Pristidae)

Figure 3. Majority-rule consensus tree of 10 000 bootstrap pseudoreplicates constructed using maximum parsimony based on 480-bp sequences of the mitochondrial DNA gene NADH-2 of sawfish specimens sampled along the geographical range of the group. Clades with high bootstrap support are coloured with geographical origin noted. Outgroup species included in the analyses were Aetobatus narinari, Raja rhina, Dasyatis annotata, and Rhizoprionodon porosus (available from G. Naylor's database).

Figure 2 in Species delineation and global population structure of Critically Endangered sawfishes (Pristidae)

Figure 2. Plot of Pristis spp. individuals projected onto the first two canonical factors for visualization of the ordering of the taxa in the multivariate space based on body morphometrics and number of rostral teeth. Pristis pristis group dots are coloured by ocean basin: Atlantic in red, Indo-West Pacific in orange, and Eastern Pacific in black; other Pristis species are coloured as follows: Pristis zijsron in blue, Pristis pectinata in green, and Pristis clavata in grey.

Figure 1 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 1. Sampling of Steno bredanensis for this study. Black circles, new control region sequences; white circles, sequences available in GenBank. The inset shows sampling localities in the South Western Atlantic (SW Atl). CS Pac, central southern Pacific; ET Pac, eastern tropical Pacific; Car, Caribbean; NW Pac, northwestern Pacific; Ind, Indian Ocean; CE, Ceará State; ES, Espírito Santo State; RJ, Rio de Janeiro State; RS, Rio Grande do Sul State; SC, Santa Catarina State.

Figure 2 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 2. Median-joining network of Steno bredanensis mtDNA control region haplotypes (N = 112). Circle size is proportional to frequency. Branch length reflects molecular distance. CE, Ceará State; ES, Espírito Santo State; RJ, Rio de Janeiro State; RS, Rio Grande do Sul State; SC, Santa Catarina State.

Figure 5 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 5. Intra- and interspecific genetic distances (Kimura two-parameter, K2P) in the cytochrome b sequences of delphinids, and the divergence between Steno bredanensis in the Atlantic and Pacific/Indian Oceans.

Figure 7 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 7. Intra- and interspecific genetic distances (Kimura two-parameter, K2P) in the mitogenomes of delphinids, and the divergence between Steno bredanensis in the Atlantic and Pacific Oceans.

Figure 4 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 4. Phylogenetic neighbour-joining (NJ) tree of delphinid cytochrome b sequences. Numbers above branches indicate bootstrap/posterior probability values>75% (NJ, Kimura two-parameter/Bayesian, Hasegawa-Kishino-Yano + gamma + invariant sites).

Figure 3 in Molecular taxonomy and population structure of the rough-toothed dolphin Steno bredanensis (Cetartiodactyla: Delphinidae)

Figure 3. Phylogenetic tree (neighbour-joining, Kimura two-parameter) showing the genetic divergence between sequences of the control region of the Atlantic (ES, Espírito Santo State; RJ, Rio de Janeiro State; SC, Santa Catarina State; RS, Rio Grande do Sul State) and other regions analysed (Pacific and Indian Oceans). Numbers at nodes correspond to bootstrap values>75% (10 000 replicates). CS Pac, central southern Pacific; ET Pac, eastern tropical Pacific; NW Pac, northwestern Pacific; CE, Ceará State; Sb, Steno bredanensis. MQ and BG are field codes for samples from RJ. The scale bar shows the length of branch that corresponds to a Kimura two-parameter distance of 0.005.

opencc-zeroOct 2021View details →

Microsatellites data set: Correlated population genetic structure in a three-tiered host-parasite system: the potential for coevolution and adaptive divergence

Three subspecies of Northern Bahamian Rock Iguanas, Cyclura cychlura, are currently recognized: C. c. cychlura,restricted to Andros Island, and C. c. figginsi and C. c. inornata, native to the Exuma Island chain. Populations on Andros are genetically distinct from Exuma Island populations, yet genetic divergence among populations in the Exumas is inconsistent with the two currently recognized subspecies from those islands. The potential consequences of this discrepancy might include the recognition of a single subspecies throughout the Exumas rather than two. That inference also ignores evidence that populations of C. cychlura are potentially adaptively divergent. We compared patterns of population relatedness in a three-tiered host-parasite system: C. cychlura iguanas, their ticks (genus Amblyomma, preferentially parasitizing these reptiles), and Rickettsia spp. endosymbionts (within tick ectoparasites). Our results indicate that while C. c. cychlura on Andros is consistently supported as a separate clade, patterns of relatedness among populations of C. c. figginsi and C. c. inornata within the Exuma Island chain are more complex. The distribution of the hosts, different tick species, and Rickettsia spp., supports the evolutionary independence of C. c. inornata. Further, these patterns are also consistent with two independent evolutionarily significant units within C. c. figginsi. Our findings suggest coevolutionary relationships between the reptile hosts, their ectoparasites, and rickettsial organisms, suggesting local adaptation. This work also speaks to the limitations of using neutral molecular markers from a single focal taxon as the sole currency for recognizing evolutionary novelty in populations of endangered species.

opencc-zeroOct 2022View details →

Code from: A theoretical framework for trait-based eco-evolutionary dynamics: population structure, intraspecific variation, and community assembly

How is trait diversity in a community apportioned between and within co-evolving species? Disruptive selection may result in either a few species with large intraspecific trait variation (ITV) or many species with different mean traits but little ITV. Similar questions arise in spatially structured communities: heterogeneous environments could result in either a few species that exhibit local adaptation or many species with different mean traits but little local adaptation. To date, theory has been well-equipped to either include ITV or to dynamically determine the number of coexisting species, but not both. Here, we devise a theoretical framework that combines these facets, and apply it to the above questions of how trait variation is apportioned within and between species in unstructured and structured populations, using two simple models of Lotka-Volterra competition. For unstructured communities, we find that as the breadth of the resource spectrum increases, ITV goes from being unimportant to crucial for characterizing the community. For spatially structured communities on two patches, we find no local adaptation, symmetric local adaptation, or asymmetric local adaptation depending on how much the patches differ. Our framework provides a general approach to incorporate ITV in models of eco-evolutionary community assembly.

opencc-by-4.0Oct 2022View details →

Population structure and genetic variation of fragmented mountain birch forests in Iceland

Data avilability for the manuscript JOH-2022-096.R2 accepted for application