Joint species distribution modeling reveals a changing prey landscape for North Pacific right whales on the Bering shelf.

The eastern North Pacific right whale (NPRW) is the most endangered population of whale and has been observed north of its core feeding ground in recent years with low sea ice extent. Sea ice and water temperature are important drivers for zooplankton dynamics within the whale's core feeding ground in the southeastern Bering Sea, seasonally forming stable fronts along the shelf that give rise to distinct zooplankton communities. A northward shift in NPRW distribution driven by changing distribution of prey resources could put this species at increased risk of entanglement and vessel strikes. We modeled the abundance of NPRW prey, Calanus glacialis, Neocalanus, and Thysanoessa species, using a dynamic biophysical food web model of nine zooplankton guilds in the Bering shelf zooplankton community during a period of warming (2006-2016). This model is unique among prior zooplankton studies from the region in that it includes density dependence, thereby allowing us to ask whether species interactions influence zooplankton dynamics. Modeling confirmed the importance of sea ice and ocean temperature to zooplankton dynamics in the region. Density-independent growth drove community dynamics, while dependent factors were comparatively minimal. Overall, Calanus responded to environment terms, with the strength and direction of response driven by copepodite stage. Neocalanus and Thysanoessa responses were weaker, likely due to their primary occurrence on the outer shelf. We also modeled the steady-state (equilibrium) abundance of Calanus in conditions with and without wind gusts to test whether advection of outer shelf species might disrupt the steady-state dynamics of Calanus abundance; the results did not support disruption. Given the annual fall sampling design, we interpret our results as follows: low-ice-extent winters induced stronger spring winds and weakened fronts on the shelf, thereby advecting some outer shelf species into the study region; increased development rates in these warm conditions influenced the proportion of C. glacialis copepodite stages over the season. Residual correlation suggests missing drivers, possibly predators, and phytoplankton bloom composition. Given the continued loss of sea ice in the region and projected continued warming, our findings suggest that C. glacialis will move northward, and thus, whales may move northward to continue targeting them.

Machine-learning-based simultaneous detection and ranging of impulsive baleen whale vocalizations using a single hydrophone.

The low-frequency impulsive gunshot vocalizations of baleen whales exhibit dispersive propagation in shallow-water channels which is well-modeled by normal mode theory. Typically, underwater acoustic source range estimation requires multiple time-synchronized hydrophone arrays which can be difficult and expensive to achieve. However, single-hydrophone modal dispersion has been used to range baleen whale vocalizations and estimate shallow-water geoacoustic properties. Although convenient when compared to sensor arrays, these algorithms require preliminary signal detection and human labor to estimate the modal dispersion. In this paper, we apply a temporal convolutional network (TCN) to spectrograms from single-hydrophone acoustic data for simultaneous gunshot detection and ranging. The TCN learns ranging and detection jointly using gunshots simulated across multiple environments and ranges along with experimental noise. The synthetic data are informed by only the water column depth, sound speed, and density of the experimental environment, while other parameters span empirically observed bounds. The method is experimentally verified on North Pacific right whale gunshot data collected in the Bering Sea. To do so, 50 dispersive gunshots were manually ranged using the state-of-the-art time-warping inversion method. The TCN detected these gunshots among 50 noise-only examples with high precision and estimated ranges which closely matched those of the physics-based approach.

Oxylipin responses to fasting and insulin infusion in a large mammalian model of fasting-induced insulin resistance, the northern elephant seal.

The prolonged, postweaning fast of northern elephant seal (Mirounga angustirostris) pups is characterized by a reliance on lipid metabolism and reversible, fasting-induced insulin resistance, providing a unique model to examine the effects of insulin on lipid metabolism. We have previously shown that acute insulin infusion induced a shift in fatty acid metabolism dependent on fasting duration. This study complements the previous study by examining the effects of fasting duration and insulin infusion on circulating levels of oxylipins, bioactive metabolites derived from the oxygenation of polyunsaturated fatty acids. Northern elephant seal pups were studied at two postweaning periods (n = 5/period): early fasting (1-2 wk postweaning; 127 ± 1 kg) and late fasting (6-7 wk postweaning; 93 ± 4 kg). Different cohorts of pups were weighed, sedated, and infused with 65 mU/kg of insulin. Plasma was collected prior to infusion (T0) and at 10, 30, 60, and 120 min postinfusion. A profile of ∼80 oxylipins was analyzed by UPLC-ESI-MS/MS. Nine oxylipins changed between early and late fasting and eight were altered in response to insulin infusion. Fasting decreased prostaglandin F2α (PGF2α) and increased 14,15-dihydroxyicosatrienoic acid (14,15-DiHETrE), 20-hydroxyeicosatetraenoic acid (20-HETE), and 4-hydroxy-docosahexaenoic acid (4-HDoHE) (P < 0.03) in T0 samples, whereas insulin infusion resulted in an inverse change in area-under-the-curve (AUC) levels in these same metabolites (P < 0.05). In addition, 12-12-hydroperoxyeicosatetraenoic acid (HpETE) and 12-HETE decreased with fasting and insulin infusion, respectively (P < 0.04). The oxylipins altered during fasting and in response to insulin infusion may contribute to the manifestation of insulin resistance and participate in the metabolic regulation of associated cellular processes.

Classification of dispersive gunshot calls using a convolutional neural network.

A convolutional neural network (CNN) was trained to identify multi-modal gunshots (impulse calls) within large acoustic datasets in shallow-water environments. South Atlantic right whale gunshots were used to train the CNN, and North Pacific right whale (NPRW) gunshots, to which the network was naive, were used for testing. The classifier generalizes to new gunshots from the NPRW and is shown to identify calls which can be used to invert for source range and/or environmental parameters. This can save human analysts hours of manually screening large passive acoustic monitoring datasets.

COVID-19 Contact Tracing in Two Counties - North Carolina, June-July 2020.

Contact tracing is a strategy implemented to minimize the spread of communicable diseases (1,2). Prompt contact tracing, testing, and self-quarantine can reduce the transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) (3,4). Community engagement is important to encourage participation in and cooperation with SARS-CoV-2 contact tracing (5). Substantial investments have been made to scale up contact tracing for COVID-19 in the United States. During June 1-July 12, 2020, the incidence of COVID-19 cases in North Carolina increased 183%, from seven to 19 per 100,000 persons per day* (6). To assess local COVID-19 contact tracing implementation, data from two counties in North Carolina were analyzed during a period of high incidence. Health department staff members investigated 5,514 (77%) persons with COVID-19 in Mecklenburg County and 584 (99%) in Randolph Counties. No contacts were reported for 48% of cases in Mecklenburg and for 35% in Randolph. Among contacts provided, 25% in Mecklenburg and 48% in Randolph could not be reached by telephone and were classified as nonresponsive after at least one attempt on 3 consecutive days of failed attempts. The median interval from specimen collection from the index patient to notification of identified contacts was 6 days in both counties. Despite aggressive efforts by health department staff members to perform case investigations and contact tracing, many persons with COVID-19 did not report contacts, and many contacts were not reached. These findings indicate that improved timeliness of contact tracing, community engagement, and increased use of community-wide mitigation are needed to interrupt SARS-CoV-2 transmission.

Nonlinear time-warping made simple: A step-by-step tutorial on underwater acoustic modal separation with a single hydrophone.

Classical ocean acoustic experiments involve the use of synchronized arrays of sensors. However, the need to cover large areas and/or the use of small robotic platforms has evoked interest in single-hydrophone processing methods for localizing a source or characterizing the propagation environment. One such processing method is "warping," a non-linear, physics-based signal processing tool dedicated to decomposing multipath features of low-frequency transient signals (frequency f < 500 Hz), after their propagation through shallow water (depth D < 200 m) and their reception on a distant single hydrophone (range r > 1 km). Since its introduction to the underwater acoustics community in 2010, warping has been adopted in the ocean acoustics literature, mostly as a pre-processing method for single receiver geoacoustic inversion. Warping also has potential applications in other specialties, including bioacoustics; however, the technique can be daunting to many potential users unfamiliar with its intricacies. Consequently, this tutorial article covers basic warping theory, presents simulation examples, and provides practical experimental strategies. Accompanying supplementary material provides matlab code and simulated and experimental datasets for easy implementation of warping on both impulsive and frequency-modulated signals from both biotic and man-made sources. This combined material should provide interested readers with user-friendly resources for implementing warping methods into their own research.

Song production by the North Pacific right whale, Eubalaena japonica.

This paper describes song production by the eastern North Pacific right whale (NPRW, Eubalaena japonica) in the southeastern Bering Sea. Songs were localized in real-time to individuals using sonobuoys. Singers whose sex could be determined were all males. Autonomous recorder data from 17 year-long deployments were analyzed to document and characterize song types. Four distinct song types were documented over eight years (2009-2017) at five distinct locations. Each song type consists of a hierarchical structure of 1-3 different repeating phrases comprised predominantly of gunshot sounds; three of the four songs contained additional sound types (downsweep, moan, and low-frequency pulsive call). Songs were detected annually (July-January); all song types remained consistent over eight years. Two different songs often occurred simultaneously, produced by different individuals; the same song was never detected simultaneously at the same location. The same song type was detected on the same day and time at two distant locations, indicating multiple individuals can produce the same song. These findings provide support that males produce song; it remains unknown if females also sing. NPRW is the first right whale species documented to produce song. Based on current knowledge about song in mysticetes, it is hypothesized that these songs are reproductive displays.

Using nonlinear time warping to estimate North Pacific right whale calling depths in the Bering Sea.

Calling depth distributions are estimated for two types of calls produced by critically endangered eastern North Pacific right whales (NPRWs) in the Bering Sea, using passive acoustic data collected with bottom-mounted hydrophone recorders. Nonlinear time resampling of 12 NPRW "upcalls" and 20 "gunshots" recorded in a critical NPRW habitat isolated individual normal mode arrivals from each call. The relative modal arrival times permitted range estimates between 1 and 40 km, while the relative modal amplitudes permitted call depth estimates, provided that environmental inversions were obtained from high signal-to-noise ratio calls. Gunshot sounds were generally only produced at a few meters depth, while upcall depths clustered between 10 and 25 m, consistent with previously published bioacoustic tagging results from North Atlantic right whales. A Wilcoxon rank sum test rejected the null hypothesis that the mean calling depths of the two call types were the same (p = 2.9 × 10-5); the null hypothesis was still rejected if the sample set was restricted to one call per acoustic encounter (p = 0.02). Propagation modeling demonstrates that deeper depths enhance acoustic propagation and that source depth estimates impact both NPRW upcall source level and detection range estimates.

Community-Based Diabetes Screening and Risk Assessment in Rural West Virginia.

This project utilized a cross-sectional study design to assess diabetes risk among 540 individuals from 12 counties using trained extension agents and community organizations in West Virginia. Individuals were screened for diabetes using (1) the validated 7-item diabetes risk assessment survey and (2) hemoglobin A1c tests. Demographic and lifestyle behaviors were also collected. The average age, body mass index, and A1c were 51.2 ± 16.4, 31.1 ± 7.5, and 5.8 ± 0.74, respectively. The majority were females, Non-Hispanic Whites with no prior diagnosis of diabetes. Screenings showed that 61.8% of participants were at high risk for diabetes. Family history of diabetes (siblings or parents), overweight or obese status, sedentary lifestyle, and older age were commonly prevalent risk factors. Higher risk scores computed from the 7-item questions correlated positively with higher A1c (r = 0.221, P < 0.001). In multivariate logistic regression analyses, higher diabetes risk was predicted by obesity, older age, family history of hypertension, and gestational diabetes. Females were 4 times at higher risk than males. The findings indicated that community-based screenings were an effective way to assess diabetes risk in rural West Virginia. Linking diabetes screenings with referrals to lifestyle programs for high risk individuals can help reduce the burden of diabetes in the state.

In situ measurements of phytoplankton fluorescence using low cost electronics.

Chlorophyll a fluorometry has long been used as a method to study phytoplankton in the ocean. In situ fluorometry is used frequently in oceanography to provide depth-resolved estimates of phytoplankton biomass. However, the high price of commercially manufactured in situ fluorometers has made them unavailable to some individuals and institutions. Presented here is an investigation into building an in situ fluorometer using low cost electronics. The goal was to construct an easily reproducible in situ fluorometer from simple and widely available electronic components. The simplicity and modest cost of the sensor makes it valuable to students and professionals alike. Open source sharing of architecture and software will allow students to reconstruct and customize the sensor on a small budget. Research applications that require numerous in situ fluorometers or expendable fluorometers can also benefit from this study. The sensor costs US$150.00 and can be constructed with little to no previous experience. The sensor uses a blue LED to excite chlorophyll a and measures fluorescence using a silicon photodiode. The sensor is controlled by an Arduino microcontroller that also serves as a data logger.

Radiated noise from commercial ships in the Gulf of Maine: implications for whale/vessel collisions.

To understand mysticete acoustic-based detection of ships, radiated noise from high-speed craft, cruise ships, catamarans and fishing vessels was recorded June-September 2009. Calibrated acoustic data (<2500 Hz) from a vertical hydrophone array was combined with ship passage information. A cruise ship had the highest broadband source level, while a fishing vessel had the lowest. Ship noise radiated asymmetrically and varied with depth. Bow null-effect acoustic shadow zones were observed for all ship classes and were correlated with ship-length-to-draft-ratios. These shadow zones may reduce ship detection by near-surface mysticetes.

Mutations in a P-type ATPase gene cause axonal degeneration.

Neuronal loss and axonal degeneration are important pathological features of many neurodegenerative diseases. The molecular mechanisms underlying the majority of axonal degeneration conditions remain unknown. To better understand axonal degeneration, we studied a mouse mutant wabbler-lethal (wl). Wabbler-lethal (wl) mutant mice develop progressive ataxia with pronounced neurodegeneration in the central and peripheral nervous system. Previous studies have led to a debate as to whether myelinopathy or axonopathy is the primary cause of neurodegeneration observed in wl mice. Here we provide clear evidence that wabbler-lethal mutants develop an axonopathy, and that this axonopathy is modulated by Wld(s) and Bax mutations. In addition, we have identified the gene harboring the disease-causing mutations as Atp8a2. We studied three wl alleles and found that all result from mutations in the Atp8a2 gene. Our analysis shows that ATP8A2 possesses phosphatidylserine translocase activity and is involved in localization of phosphatidylserine to the inner leaflet of the plasma membrane. Atp8a2 is widely expressed in the brain, spinal cord, and retina. We assessed two of the mutant alleles of Atp8a2 and found they are both nonfunctional for the phosphatidylserine translocase activity. Thus, our data demonstrate for the first time that mutation of a mammalian phosphatidylserine translocase causes axon degeneration and neurodegenerative disease.