Group versus population level demographics: An analysis of comparability using long term data on wild white‐faced capuchin monkeys (Cebus capucinus imitator)

Primates have long been used as indicator species for assessing overall ecosystem health. However, area‐wide census methods are time consuming, costly, and not always feasible under many field conditions. Therefore, it is important to establish whether monitoring a subset of a population accurately reflects demographic changes occurring in the population at large. Over the past 35 years, we have conducted 15 area‐wide censuses in Sector Santa Rosa, Costa Rica. These efforts have revealed important trends in population growth patterns of capuchin monkeys following the protection and subsequent regeneration of native forests. During this same period, we have also intensively studied a subset of the capuchin groups. Comparing these two datasets, we investigate whether the population structures of the closely monitored groups are reliable indicators of area‐wide demographic patterns. We compare the overall group size and the individual age/sex class compositions of study groups and nonstudy groups (i.e., those contacted during area‐wide censuses only). Our study groups contained more individuals overall with a larger proportion of infants, and there were indications that the proportion of adult and subadult males was lower. These differences can be ascribed either to sampling errors or real differences attributable to human presence and/or better habitat quality for the study groups. No other sex/age classes differed, and major demographic changes were simultaneously evident in both study and nonstudy groups. This study suggests that the Santa Rosa capuchin population is similarly impacted by large‐scale ecological patterns observable within our study groups.     

The Empirical Analysis of Cigarette Tax Avoidance and Illicit Trade in Vietnam, 1998-2010

Illicit trade carries the potential to magnify existing tobacco-related health care costs through increased availability of untaxed and inexpensive cigarettes. What is known with respect to the magnitude of illicit trade for Vietnam is produced primarily by the industry, and methodologies are typically opaque. Independent assessment of the illicit cigarette trade in Vietnam is vital to tobacco control policy. This paper measures the magnitude of illicit cigarette trade for Vietnam between 1998 and 2010 using two methods, discrepancies between legitimate domestic cigarette sales and domestic tobacco consumption estimated from surveys, and trade discrepancies as recorded by Vietnam and trade partners. The results indicate that Vietnam likely experienced net smuggling in during the period studied. With the inclusion of adjustments for survey respondent under-reporting, inward illicit trade likely occurred in three of the four years for which surveys were available. Discrepancies in trade records indicate that the value of smuggled cigarettes into Vietnam ranges from $100 million to $300 million between 2000 and 2010 and that these cigarettes primarily originate in Singapore, Hong Kong, Macao, Malaysia, and Australia. Notable differences in trends over time exist between the two methods, but by comparison, the industry estimates consistently place the magnitude of illicit trade at the upper bounds of what this study shows. The unavailability of annual, survey-based estimates of consumption may obscure the true, annual trend over time. Second, as surveys changed over time, estimates relying on them may be inconsistent with one another. Finally, these two methods measure different components of illicit trade, specifically consumption of illicit cigarettes regardless of origin and smuggling of cigarettes into a particular market. However, absent a gold standard, comparisons of different approaches to illicit trade measurement serve efforts to refine and improve measurement approaches and estimates.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

‘Mild mitochondrial uncoupling’ induced protection against neuronal excitotoxicity requires AMPK activity

The preconditioning response conferred by a mild uncoupling of the mitochondrial membrane potential (Δψ_m) has been attributed to altered reactive oxygen species (ROS) production and mitochondrial Ca^2 + uptake within the cells. Here we have explored if altered cellular energetics in response to a mild mitochondrial uncoupling stimulus may also contribute to the protection. The addition of 100 nM FCCP for 30 min to cerebellar granule neurons (CGNs) induced a transient depolarization of the Δψ_m, that was sufficient to significantly reduce CGN vulnerability to the excitotoxic stimulus, glutamate. On investigation, the mild mitochondrial ‘uncoupling’ stimulus resulted in a significant increase in the plasma membrane levels of the glucose transporter isoform 3, with a hyperpolarisation of Δψ_m and increased cellular ATP levels also evident following the washout of FCCP. Furthermore, the phosphorylation state of AMP-activated protein kinase (AMPK) (Thr 172) was increased within 5 min of the uncoupling stimulus and elevated up to 1 h after washout. Significantly, the physiological changes and protection evident after the mild uncoupling stimulus were lost in CGNs when AMPK activity was inhibited. This study identifies an additional mechanism through which protection is mediated upon mild mitochondrial uncoupling: it implicates increased AMPK signalling and an adaptive shift in energy metabolism as mediators of the preconditioning response associated with FCCP-induced mild mitochondrial uncoupling.     

Monitoring an invasive perennial at the landscape scale with remote sensing

Summary   Worldwide, invasive weeds threaten agricultural, natural and urban ecosystems. In Australia's agricultural and grazing regions, invasive species often establish across extensive areas where weed management is hampered by an inability to detect the location and timing of an outbreak. In these vast landscapes, an effective detection and monitoring system is required to delineate the extent of the invasion and identify spatial and temporal factors associated with weed establishment and thickening. In this study, we utilize a time series of remote sensing imagery to detect the spatial and temporal patterns of Prickly Acacia ( Acacia nilotica ) invasion in the Mitchell grass plains of North Queensland. We develop a spectral index from Landsat images which is applied to images from 1989 to 2004, in combination with a classification mask, to identify locations and monitor changes in Prickly Acacia density across 29 000 km² of Mitchell grass plains. The approach identified spectral and temporal signatures consistent with Prickly Acacia infestation on 1.9% of this landscape. Field checking of results confirmed presence of the weed in previously unrecorded locations. The approach may be used to evaluate future spread, or outcomes of management strategies for Prickly Acacia in this landscape and could be employed to detect and monitor invasions in other extensive landscapes.     

Automated extraction of bank angles from bird‐borne video footage using open‐source software

The use of miniaturized video cameras to study the at‐sea behavior of flying seabirds has increased in recent years. These cameras allow researchers to record several behaviors that were not previously possible to observe. However, video recorders produce large amounts of data and videos can often be time‐consuming to analyze. We present a new technique using open‐source software to extract bank angles from bird‐borne video footage. Bank angle is a key facet of dynamic soaring, which allows albatrosses and petrels to efficiently search vast areas of ocean for food. Miniaturized video cameras were deployed on 28 Wandering Albatrosses (Diomedea exulans) on Marion Island (one of the two Prince Edward Islands) from 2016 to 2018. The OpenCV library for the Python programming language was used to extract the angle of the horizon relative to the bird’s body (= bank angle) from footage when the birds were flying using a series of steps focused on edge detection. The extracted angles were not significantly different from angles measured manually by three independent observers, thus being a valid method to measure bank angles. Image quality, high wind speeds, and sunlight all influenced the accuracy of angle estimates, but post‐processing eliminated most of these errors. Birds flew most often with cross‐winds (58%) and tailwinds (39%), resulting in skewed distributions of bank angles when birds turned into the wind more often. Higher wind speeds resulted in extreme bank angles (maximum observed was 94°). We present a novel method for measuring postural data from seabirds that can be used to describe the fine‐scale movements of the dynamic‐soaring cycle. Birds appeared to alter their bank angle in response to varying wind conditions to counter wind drift associated with the prevailing westerly winds in the Southern Ocean. These data, in combination with fine‐scale positional data, may lead to new insights into dynamic‐soaring flight.