Ileum of the Cephalotes ants: A specialized structure to harbor symbionts microorganisms

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mass occurrence of the cubomedusa Copula sivickisi (Cnidaria: Cubozoa) at Seto Harbor, Shirahama, Wakayama, Japan in summer of 2013, a recent example of global warming

More than 200 very young medusae of Copula sivickisi (Stiasny) were collected within totally 60 minutes at two nights in June, 2013 at the Seto Harbor, Shirahama, Wakayama, Japan. This mass occurrence might be related to recent global warming at Shirahama, known as the northernmost distributional locality of this cubozoan species. It is assumed that the polyp stage of this species may live in the surrounding areas, because there jellyfish were small size (most are less than 1.6 mm height) that was conceivable as the newly released one from the polyp.

Stability in The Proportion of Harbor Seals Hauled Out Under Locally Ideal Conditions

We monitored the haul-out behavior of 68 radio-tagged harbor seals (Phoca vitulina) during the molt season at two Alaskan haul-out sites (Grand Island, August-September 1994; Nanvak Bay, August-September 2000). For each site, we created a statistical model of the proportion of seals hauled out as a function of date, time of day, tide, and weather covariates. Using these models, we identified the conditions that would result in the greatest proportion of seals hauled out. Although those “ideal conditions” differed between sites, the proportion of seals predicted to be hauled out under those conditions was very similar (81.3% for Grand Island and 85.7% for Nanvak Bay). The similar estimates for both sites suggest that haul-out proportions under locally ideal conditions may be constant between years and geographic regions, at least during the molt season.

The Abundance of Harbor Seals in the Gulf of Alaska

The abundance of harbor seals (Phoca vitulina richardii) has declined in recent decades at several Alaska locations. The causes of these declines are unknown, but there is concern about the status of the populations, especially in the Gulf of Alaska. To assess the status of harbor seals in the Gulf of Alaska, we conducted aerial surveys of seals on their haul-out sites in August-September 1996. Many factors influence the propensity of seals to haul out, including tides, weather, time of day, and time of year. Because these “covariates” cannot simultaneously be controlled through survey design, we used a regression model to adjust the counts to an estimate of the number of seals that would have been ashore during a hypothetical survey conducted under ideal conditions for hauling out. The regression, a generalized additive model, not only provided an adjustment for the covariates, but also confirmed the nature and shape of the covariate effects on haul-out behavior. The number of seals hauled out was greatest at the beginning of the surveys (mid-August). There was a broad daily peak from about 1100-1400 local solar time. The greatest numbers were hauled out at low tide on terrestrial sites. Tidal state made little difference in the numbers hauled out on glacial ice, where the area available to seals did not fluctuate with the tide. Adjusting the survey counts to the ideal state for each covariate produced an estimate of 30,035 seals, about 1.8 times the total of the unadjusted counts (16,355 seals). To the adjusted count, we applied a correction factor of 1.198 from a separate study of two haul-out sites elsewhere in Alaska, to produce a total abundance estimate of 35,981 (SE 1,833). This estimate accounts both for the effect of covariates on survey counts and for the proportion of seals that remained in the water even under ideal conditions for hauling out.

Harbor Porpoise (Phocoena phocoena) Abundance in Alaska: Bristol Bay to Southeast Alaska, 1991-1993

Between 1991 and 1993, Alaska harbor porpoise (Phocoena phocoena) abundance was investigated during aerial surveys throughout much of the coastal and offshore waters from Bristol Bay in the eastern Bering Sea to Dixon Entrance in Southeast Alaska. Line-transect methodology was used, and only those observations made during optimal conditions were analyzed. Survey data indicated densities of 4.48 groups/100 km2, or approximately 3,531 harbor porpoises (95% C.I. 2,206-5,651) in Bristol Bay and 0.54 groups/100 km2, or 136 harbor porpoises (95% C.I. 11-1,645) for Cook Inlet. Efforts off Kodiak Island resulted in densities of 1.85 groups/100 km2, or an abundance estimate of 740 (95% C.I. 259-2,115). Surveys off the south side of the Alaska Peninsula found densities of 2.03 groups/100 km2 and an abundance estimate of 551 (95% C.I. 423-719). Surveys of offshore waters from Prince William Sound to Dixon Entrance yielded densities of 4.02 groups/100 km’ and an abundance estimate of 3,982 (95% C.I. 2,567-6,177). Combining all years and areas yielded an uncorrected density estimate of 3.82 porpoises per 100 km2, resulting in an abundance estimate of 8,940 porpoises (CV = 13.8%) with a 95% confidence interval of 6,746-11,848. Using correction factors from other studies to adjust for animals missed by observers, the total number of Alaska harbor porpoises is probably three times this number.

Space–time zero-inflated count models of Harbor seals

Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space–time random effects in zero-inflated Poisson (ZIP) and ‘hurdle’ models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space–time ZIP and hurdle models in a Bayesian hierarchical model. Space–time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space–time ZIP and hurdle models.

Implantation of Subcutaneous Radio Transmitters in the Harbor Seal (Phoca vitulina)

Radio telemetry has become a standard tool for studying the behavior, physiology, life history traits, and population dynamics of marine mammals. Radio transmitters typically are attached to the hind flippers of pinnipeds or glued to the fur using marine epoxy or other cyanocrylare adhesives (Fedak et al. 1983, Bengtson 1993, Jeffries et al. 1993). Longterm data acquisition is difficult, however, because radio-flipper transmitters commonly tear from the webbing of the flipper and instruments that are glued to the fur are shed during the seasonal molt.

Mutations in SRCAP, Encoding SNF2-Related CREBBP Activator Protein, Cause Floating-Harbor Syndrome

Floating-Harbor syndrome (FHS) is a rare condition characterized by short stature, delayed osseous maturation, expressive-language deficits, and a distinctive facial appearance. Occurrence is generally sporadic, although parent-to-child transmission has been reported on occasion. Employing whole-exome sequencing, we identified heterozygous truncating mutations in SRCAP in five unrelated individuals with sporadic MS. Sanger sequencing identified mutations in SRCAP in eight more affected persons. Mutations were de novo in all six instances in which parental DNA was available. SRCAP is an SNF2-related chromatin-remodeling factor that serves as a coactivator for CREB-binding protein (CREBBP, better known as CBP, the major cause of Rubinstein-Taybi syndrome [RTS]). Five SRCAP mutations, two of which are recurrent, were identified; all are tightly clustered within a small (111 codon) region of the final exon. These mutations are predicted to abolish three C-terminal AT-hook DNA-binding motifs while leaving the CBP-binding and ATPase domains intact. Our findings show that SRCAP mutations are the major cause of FHS and offer an explanation for the clinical overlap between FHS and RTS.