Vocal communication in wild chimpanzees: a call rate study

BACKGROUND: Patterns of vocal communication have implications for species conservation: a change in calling behaviour can, for instance, reflect a disturbed habitat. More importantly, call rate is a parameter that allows conservation planners to convert call density into animal density, when detecting calls with a passive acoustic monitoring system (PAM). METHODS: We investigated chimpanzee (Pan troglodytes schweinfurthii) call rate during the late dry season in the Issa Valley, western Tanzania by conducting focal follows. We examined the socio-ecological factors that influence call production rate of savanna woodland chimpanzees. RESULTS: We found that sex, proportion of time spent in a vegetation type, proportion of time spent travelling, time of the day, party size and swollen parous female presence had a significant effect on the call rate. Call rate differed among the different demographic classes with subadult and adult males vocalising twice as often as the subadult and adult females and three times as often as the juveniles. APPLICATIONS: The use of PAM and recent statistical developments to estimate animal density is promising but relies on our knowing individual call rate, often not available for many species. With the improvement in automatic call detection, we anticipate that PAM will increasingly be broadly applied to primates but also across taxa, for conservation

Wave spectra of 2D dusty plasma solids and liquids

Brownian dynamics simulations were carried out to study wave spectra of two-dimensional dusty plasma liquids and solids for a wide range of wavelengths. The existence of a longitudinal dust thermal mode was confirmed in simulations, and a cutoff wavenumber in the transverse mode was measured. Dispersion relations, resulting from simulations, were compared with those from analytical theories, such as the random-phase approximation (RPA), quasi-localized charged approximation (QLCA), and harmonic approximation (HA). An overall good agreement between the QLCA and simulations was found for wide ranges of states and wavelengths after taking into account the direct thermal effect in the QLCA, while for the RPA and HA good agreement with simulations were found in the high and low temperature limits, respectively.Comment: 26 pages, 9 figure

Advances in mapping population and demographic characteristics at small area levels

Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship of environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every ten years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution 31are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of openand big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including a) the U. S. American Community Survey, a rolling sample of the U.S. population census, b) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data, and c) the use of administrative and big data sources as proxies for demographic characteristics

Savanna Chimpanzees (Pan troglodytes schweinfurthii) Consume and Share Blue Duiker (Philantomba monticola) Meat in the Issa Valley, Ugalla, Western Tanzania

Meat eating is pervasive across chimpanzee populations in Africa, with red colobus monkey (Piliocolobus spp.) being the most common prey (Boesch & Boesch 1989; Stanford et al. 1994a; Watts et al. 2012, Hosaka 2015) if sympatric in the same habitat. Besides colobus monkeys, chimpanzees consume a variety of other primates, including olive and yellow baboons (Papio spp.) and bushbabies (Galago spp.). In the forest habitats of western Tanzania chimpanzees have been reported to consume numerous different mammalian species: 18 at Mahale Mountains National Park (Uehara 1997; Hosaka 2015) and eight at Gombe National Park, whilst in the miombo woodland dominated Ugalla Region no direct observations have been recorded to date (Table 1). In West Africa, chimpanzees from Taï Forest, Ivory Coast consume eight different mammal species, all primates (Boesch & Boesch 1989). Wherever chimpanzees consume meat, it is almost always via hunting, as they rarely scavenge (Watts 2008)

An evaluation of the factors affecting ‘poacher’ detection with drones and the efficacy of machine-learning for detection

Drones are being increasingly used in conservation to tackle the illegal poaching of animals. An important aspect of using drones for this purpose is establishing the technological and the environmental factors that increase the chances of success when detecting poachers. Recent studies focused on investigating these factors, and this research builds upon this as well as exploring the efficacy of machine-learning for automated detection. In an experimental setting with voluntary test subjects, various factors were tested for their effect on detection probability: camera type (visible spectrum, RGB, and thermal infrared, TIR), time of day, camera angle, canopy density, and walking/stationary test subjects. The drone footage was analysed both manually by volunteers and through automated detection software. A generalised linear model with a logit link function was used to statistically analyse the data for both types of analysis. The findings concluded that using a TIR camera improved detection probability, particularly at dawn and with a 90° camera angle. An oblique angle was more effective during RGB flights, and walking/stationary test subjects did not influence detection with both cameras. Probability of detection decreased with increasing vegetation cover. Machine-learning software had a successful detection probability of 0.558, however, it produced nearly five times more false positives than manual analysis. Manual analysis, however, produced 2.5 times more false negatives than automated detection. Despite manual analysis producing more true positive detections than automated detection in this study, the automated software gives promising, successful results, and the advantages of automated methods over manual analysis make it a promising tool with the potential to be successfully incorporated into anti-poaching strategies

Cloning, sequencing and analysis of the enterocin biosynthesis gene cluster from the marine isolate ‘Streptomyces maritimus’: evidence for the derailment of an aromatic polyketide synthase

AbstractBackground: Polycyclic aromatic polyketides, such as the tetracyclines and anthracyclines, are synthesized by bacterial aromatic polyketide synthases (PKSs). Such PKSs contain a single set of iteratively used individual proteins for the construction of a highly labile poly-β-carbonyl intermediate that is cyclized by associated enzymes to the core aromatic polyketide. A unique polyketide biosynthetic pathway recently identified in the marine strain ‘Streptomyces maritimus’ deviates from the normal aromatic PKS model in the generation of a diverse series of chiral, non-aromatic polyketides.Results: A 21.3 kb gene cluster encoding the biosynthesis of the enterocin and wailupemycin family of polyketides from ‘S. maritimus’ has been cloned and sequenced. The biosynthesis of these structurally diverse polyketides is encoded on a 20 open reading frames gene set containing a centrally located aromatic PKS. The architecture of this novel type II gene set differs from all other aromatic PKS clusters by the absence of cyclase and aromatase encoding genes and the presence of genes encoding the biosynthesis and attachment of the unique benzoyl-CoA starter unit. In addition to the previously reported heterologous expression of the gene set, in vitro and in vivo expression studies with the cytochrome P-450 EncR and the ketoreductase EncD, respectively, support the involvement of the cloned genes in enterocin biosynthesis.Conclusions: The enterocin biosynthesis gene cluster represents the most versatile type II PKS system investigated to date. A large series of divergent metabolites are naturally generated from the single biochemical pathway, which has several metabolic options for creating structural diversity. The absence of cyclase and aromatase gene products and the involvement of an oxygenase-catalyzed Favorskii-like rearrangement provide insight into the observed spontaneity of this pathway. This system provides the foundation for engineering hybrid expression sets in the generation of structurally novel compounds for use in drug discovery

Small-area methods for investigation of environment and health

Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographic scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast growing computational capabilities permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered, and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases

Disease mapping of early- and late-stage cancer to monitor inequalities in early detection: a study of cutaneous malignant melanoma

We consider disease mapping of early- and late-stage cancer, in order to identify and monitor inequalities in early detection. Our method is demonstrated by mapping cancer incidence at high geographical resolution using data on 10,302 cutaneous malignant melanoma (CMM) cases within the 3.7 million population of South-West Sweden. The cases were geocoded into small-areas, each with a population size between 600 and 2600 and accessible socio-demographic data. Using the disease mapping application Rapid Inquiry Facility (RIF) 4.0, we produced regional maps to visualise spatial variations in stage I, II and III–IV CMM incidences, complemented by local maps to explore the variations within two urban areas. Pronounced spatial disparities in stage I CMM incidence were revealed by the regional and local maps. Stage I CMM incidence was markedly higher in wealthier small-areas, in particular within each urban area. A twofold higher stage I incidence was observed, on average, in the wealthiest small-areas (upper quintile) than in the poorest small-areas (lower quintile). We identified in the regional map of stage III–IV CMM two clusters of higher or lower than expected late-stage incidences which were quite distinct from those identified for stage I. In conclusion, our analysis of CMM incidences supported the use of this method of cancer stage incidence mapping for revealing geographical and socio-demographic disparities in cancer detection

Population status of chimpanzees in the Masito-Ugalla Ecosystem, Tanzania.

More than 75 percent of Tanzania's chimpanzees live at low densities on land outside national parks. Chimpanzees are one of the key conservation targets in the region and long-term monitoring of these populations is essential for assessing the overall status of ecosystem health and the success of implemented conservation strategies. We aimed to assess change in chimpanzee density within the Masito-Ugalla Ecosystem (MUE) by comparing results of re-walking the same line transects in 2007 and 2014. We further used published remote sensing data derived from Landsat satellites to assess forest cover change within a 5 km buffer of these transects over that same period. We detected no statistically significant decline in chimpanzee density across the surveyed areas of MUE between 2007 and 2014, although the overall mean density of chimpanzees declined from 0.09 individuals/km(2) in 2007 to 0.05 individuals/km(2) in 2014. Whether this change is biologically meaningful cannot be determined due to small sample sizes and large, entirely overlapping error margins. It is therefore possible that the MUE chimpanzee population has been stable over this period and indeed in some areas (Issa Valley, Mkanga, Kamkulu) even showed an increase in chimpanzee density. Variation in chimpanzee habitat preference for ranging or nesting could explain variation in density at some of the survey sites between 2007 and 2014. We also found a relationship between increasing habitat loss and lower mean chimpanzee density. Future surveys will need to ensure a larger sample size, broader geographic effort, and random survey design, to more precisely determine trends in MUE chimpanzee density and population size over time. Am. J. Primatol. © 2015 Wiley Periodicals, Inc