Social networks based on frequency of roost cohabitation do not reflect association rates of Myotis lucifugus within their roosts

Bats are a group of mammals well known for forming dynamic social groups. Studies of bat social structures are often based upon the frequency at which bats occupy the same roosts because observing bats directly is not always possible. However, it is not always clear how closely bats occupying the same roost associate with each other, obscuring whether associations result from social relationships or factors such as shared preferences for roosts. Our goal was to determine if bats cohabitating buildings were also found together inside roosts by using anti‐collision technology for PIT tags, which enables simultaneous detection of multiple tags. We PIT‐tagged 293 female little brown myotis (Myotis lucifugus) and installed antennas within two buildings used as maternity roosts in Yellowstone National Park. Antennas were positioned at roost entryways to generate cohabitation networks and along regions of attic ceilings in each building to generate intraroost networks based on proximity of bats to each other. We found that intraroost and cohabitation networks of buildings were significantly correlated, with the same bats tending to be linked in both networks, but that bats cohabitating the same building often roosted apart, leading to differing assessments of social structure. Cohabitation rates implied that bats associate with a greater number of their roost‐mates than was supported by observations within the roost. This caused social networks built upon roost cohabitation rates to be denser, smaller in diameter, and contain nodes with higher average degree centrality. These results show that roost cohabitation does not reflect preference for roost‐mates in little brown myotis, as is often inferred from similar studies, and that social network analyses based on cohabitation may provide misleading results.     

Gaussian curvature analysis allows for automatic block placement in multi-block hexahedral meshing

Musculoskeletal finite element analysis (FEA) has been essential to research in orthopaedic biomechanics. The generation of a volumetric mesh is often the most challenging step in a FEA. Hexahedral meshing tools that are based on a multi-block approach rely on the manual placement of building blocks for their mesh generation scheme. We hypothesise that Gaussian curvature analysis could be used to automatically develop a building block structure for multi-block hexahedral mesh generation. The Automated Building Block Algorithm incorporates principles from differential geometry, combinatorics, statistical analysis and computer science to automatically generate a building block structure to represent a given surface without prior information. We have applied this algorithm to 29 bones of varying geometries and successfully generated a usable mesh in all cases. This work represents a significant advancement in automating the definition of building blocks.     

Systematics of Old World Odontacolus Kieffer s.l. (Hymenoptera,Platygastridae s.l.): parasitoids?of?spider?eggs

The genera Odontacolus Kieffer and Cyphacolus Priesner are among the most distinctive platygastroid wasps because of their laterally compressed metasomal horn; however, their generic status has remained unclear. We present a morphological phylogenetic analysis comprising all 38 Old World and four Neotropical Odontacolus species and 13 Cyphacolus species, which demonstrates that the latter is monophyletic but nested within a somewhat poorly resolved Odontacolus. Based on these results Cyphacolus syn. n. is placed as a junior synonym of Odontacolus which is here redefined. The taxonomy of Old World Odontacolus s.str. is revised; the previously known species Odontacolus longiceps Kieffer (Seychelles), Odontacolus markadicus Veenakumari (India), Odontacolus spinosus (Dodd) (Australia) and Odontacolus hackeri (Dodd) (Australia) are re-described, and 32 new species are described: Odontacolus africanus Valerio & Austin sp. n. (Congo, Guinea, Kenya, Madagascar, Mozambique, South Africa, Uganda, Zimbabwe), Odontacolus aldrovandii Valerio & Austin sp. n. (Nepal), Odontacolus anningae Valerio & Austin sp. n. (Cameroon), Odontacolus australiensis Valerio & Austin sp. n. (Australia), Odontacolus baeri Valerio & Austin sp. n. (Australia), Odontacolus berryae Valerio & Austin sp. n. (Australia, New Zealand, Norfolk Island), Odontacolus bosei Valerio & Austin sp. n. (India, Malaysia, Sri Lanka), Odontacolus cardaleae Valerio & Austin sp. n. (Australia), Odontacolus darwini Valerio & Austin sp. n. (Thailand), Odontacolus dayi Valerio & Austin sp. n. (Indonesia), Odontacolus gallowayi Valerio & Austin sp. n. (Australia), Odontacolus gentingensis Valerio & Austin sp. n. (Malaysia), Odontacolus guineensis Valerio & Austin sp. n. (Guinea), Odontacolus harveyi Valerio & Austin sp. n. (Australia), Odontacolus heratyi Valerio & Austin sp. n. (Fiji), Odontacolus heydoni Valerio & Austin sp. n. (Malaysia, Thailand), Odontacolus irwini Valerio & Austin sp. n. (Fiji), Odontacolus jacksonae Valerio & Austin sp. n. (Cameroon, Guinea, Madagascar), Odontacolus kiau Valerio & Austin sp. n. (Papua New Guinea), Odontacolus lamarcki Valerio & Austin sp. n. (Thailand), Odontacolus madagascarensis Valerio & Austin sp. n. (Madagascar), Odontacolus mayri Valerio & Austin sp. n. (Indonesia, Thailand), Odontacolus mot Valerio & Austin sp. n. (India), Odontacolus noyesi Valerio & Austin sp. n. (India, Indonesia), Odontacolus pintoi Valerio & Austin sp. n. (Australia, New Zealand, Norfolk Island), Odontacolus schlingeri Valerio & Austin sp. n. (Fiji), Odontacolus sharkeyi Valerio & Austin sp. n. (Thailand), Odontacolus veroae Valerio & Austin sp. n. (Fiji), Odontacolus wallacei Valerio & Austin sp. n. (Australia, Indonesia, Malawi, Papua New Guinea), Odontacolus whitfieldi Valerio & Austin sp. n. (China, India, Indonesia, Sulawesi, Malaysia, Thailand, Vietnam), Odontacolus zborowskii Valerio & Austin sp. n. (Australia), and Odontacolus zimi Valerio & Austin sp. n. (Madagascar). In addition, all species of Cyphacolus are here transferred to Odontacolus: Odontacolus asheri (Valerio, Masner & Austin) comb. n. (Sri Lanka), Odontacolus axfordi (Valerio, Masner & Austin) comb. n. (Australia), Odontacolus bhowaliensis (Mani & Mukerjee) comb. n. (India), Odontacolus bouceki (Austin & Iqbal) comb. n. (Australia), Odontacolus copelandi (Valerio, Masner & Austin) comb. n. (Kenya, Nigeria, Zimbabwe, Thailand), Odontacolus diazae (Valerio, Masner & Austin) comb. n. (Kenya), Odontacolus harteni (Valerio, Masner & Austin) comb. n. (Yemen, Ivory Coast, Paskistan), Odontacolus jenningsi (Valerio, Masner & Austin) comb. n. (Australia), Odontacolus leblanci (Valerio, Masner & Austin) comb. n. (Guinea), Odontacolus lucianae (Valerio, Masner & Austin) comb. n. (Ivory Coast, Madagascar, South Africa, Swaziland, Zimbabwe), Odontacolus normani (Valerio, Masner & Austin) comb. n. (India, United Arab Emirates), Odontacolus sallyae (Valerio, Masner & Austin) comb. n. (Australia), Odontacolus tessae (Valerio, Masner & Austin) comb. n. (Australia), Odontacolus tullyae (Valerio, Masner & Austin) comb. n. (Australia), Odontacolus veniprivus (Priesner) comb. n. (Egypt), and Odontacolus watshami (Valerio, Masner & Austin) comb. n. (Africa, Madagascar). Two species of Odontacolus are transferred to the genus Idris Förster: Idris longispinosus (Girault) comb. n. and Idris amoenus (Kononova) comb. n., and Odontacolus doddi Austin syn. n. is placed as a junior synonym of Odontacolus spinosus (Dodd). Odontacolus markadicus, previously only known from India, is here recorded from Brunei, Malaysia, Sri Lanka, Thailand and Vietnam. The relationships, distribution and biology of Odontacolus are discussed, and a key is provided to identify all species.     

Low Level of Sequence Diversity at Merozoite Surface Protein-1 Locus of Plasmodium ovale curtisi and P. ovale wallikeri from Thai Isolates

Background

The merozoite surface protein-1 (MSP-1) is a candidate target for the development of blood stage vaccines against malaria. Polymorphism in MSP-1 can be useful as a genetic marker for strain differentiation in malarial parasites. Although sequence diversity in the MSP-1 locus has been extensively analyzed in field isolates of Plasmodium falciparum and P. vivax, the extent of variation in its homologues in P. ovale curtisi and P. ovale wallikeri, remains unknown.

Methodology/Principal Findings

Analysis of the mitochondrial cytochrome b sequences of 10 P. ovale isolates from symptomatic malaria patients from diverse endemic areas of Thailand revealed co-existence of P. ovale curtisi (n = 5) and P. ovale wallikeri (n = 5). Direct sequencing of the PCR-amplified products encompassing the entire coding region of MSP-1 of P. ovale curtisi (PocMSP-1) and P. ovale wallikeri (PowMSP-1) has identified 3 imperfect repeated segments in the former and one in the latter. Most amino acid differences between these proteins were located in the interspecies variable domains of malarial MSP-1. Synonymous nucleotide diversity (π_S) exceeded nonsynonymous nucleotide diversity (π_N) for both PocMSP-1 and PowMSP-1, albeit at a non-significant level. However, when MSP-1 of both these species was considered together, π_S was significantly greater than π_N (p<0.0001), suggesting that purifying selection has shaped diversity at this locus prior to speciation. Phylogenetic analysis based on conserved domains has placed PocMSP-1 and PowMSP-1 in a distinct bifurcating branch that probably diverged from each other around 4.5 million years ago.

Conclusion/Significance

The MSP-1 sequences support that P. ovale curtisi and P. ovale wallikeri are distinct species. Both species are sympatric in Thailand. The low level of sequence diversity in PocMSP-1 and PowMSP-1 among Thai isolates could stem from persistent low prevalence of these species, limiting the chance of outcrossing at this locus.     

Visual Function and Cortical Organization in Carriers of Blue Cone Monochromacy

Carriers of blue cone monochromacy have fewer cone photoreceptors than normal. Here we examine how this disruption at the level of the retina affects visual function and cortical organization in these individuals. Visual resolution and contrast sensitivity was measured at the preferred retinal locus of fixation and visual resolution was tested at two eccentric locations (2.5° and 8°) with spectacle correction only. Adaptive optics corrected resolution acuity and cone spacing were simultaneously measured at several locations within the central fovea with adaptive optics scanning laser ophthalmoscopy (AOSLO). Fixation stability was assessed by extracting eye motion data from AOSLO videos. Retinotopic mapping using fMRI was carried out to estimate the area of early cortical regions, including that of the foveal confluence. Without adaptive optics correction, BCM carriers appeared to have normal visual function, with normal contrast sensitivity and visual resolution, but with AO-correction, visual resolution was significantly worse than normal. This resolution deficit is not explained by cone loss alone and is suggestive of an associated loss of retinal ganglion cells. However, despite evidence suggesting a reduction in the number of retinal ganglion cells, retinotopic mapping showed no reduction in the cortical area of the foveal confluence. These results suggest that ganglion cell density may not govern the foveal overrepresentation in the cortex. We propose that it is not the number of afferents, but rather the content of the information relayed to the cortex from the retina across the visual field that governs cortical magnification, as under normal viewing conditions this information is similar in both BCM carriers and normal controls.     

Evolution of larval segment position across 12 Drosophila species*

Many developmental traits that are critical to the survival of the organism are also robust. These robust traits are resistant to phenotypic change in the face of variation. This presents a challenge to evolution. In this article, we asked whether and how a well-established robust trait, Drosophila segment patterning, changed over the evolutionary history of the genus. We compared segment position scaled to body length at the first-instar larval stage among 12 Drosophila species. We found that relative segment position has changed many times across the phylogeny. Changes were frequent, but primarily small in magnitude. Phylogenetic analysis demonstrated that rates of change in segment position are variable along the Drosophila phylogenetic tree, and that these changes can occur in short evolutionary timescales. Correlation between position shifts of segments decreased as the distance between two segments increased, suggesting local control of segment position. The posterior-most abdominal segment showed the highest magnitude of change on average, had the highest rate of evolution between species, and appeared to be evolving more independently as compared to the rest of the segments. This segment was exceptionally elongated in the cactophilic species in our dataset, raising questions as to whether this change may be adaptive.