False killer whales (Pseudorca crassidens) depredate bait and catch in the Hawai‘i‐based deep‐set longline fishery, and as a result, this species is hooked or entangled more than any other cetacean ...in this fishery. We analyzed data collected by fisheries observers and from satellite‐linked transmitters deployed on false killer whales to identify patterns of odontocete depredation that could help fishermen avoid overlap with whales. Odontocete depredation was observed on ˜6% of deep‐set hauls across the fleet from 2004 to 2018. Model outcomes from binomial GAMMs suggested coarse patterns, for example, higher rates of depredation in winter, at lower latitudes, and with higher fishing effort. However, explanatory power was low, and no covariates were identified that could be used in a predictive context. The best indicator of depredation was the occurrence of depredation on a previous set of the same vessel. We identified spatiotemporal scales of this repeat depredation to provide guidance to fishermen on how far to move or how long to wait to reduce the probability of repeated interactions. The risk of depredation decreased with both space and time from a previous occurrence, with the greatest benefits achieved by moving ˜400 km or waiting ˜9 d, which reduced the occurrence of depredation from 18% to 9% (a 50% reduction). Fishermen moved a median 46 km and waited 4.7 h following an observed depredation interaction, which our analysis suggests is unlikely to lead to large reductions in risk. Satellite‐tagged pelagic false killer whales moved up to 75 km in 4 h and 335 km in 24 h, suggesting that they can likely keep pace with longline vessels for at least four hours and likely longer. We recommend fishermen avoid areas of known depredation or bycatch by moving as far and as quickly as practical, especially within a day or two of the depredation or bycatch event. We also encourage captains to communicate depredation and bycatch occurrence to enable other vessels to similarly avoid high‐risk areas.
Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ ...and remotely sensed oceanic variables (both are considered “measured data”), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.
The western Pacific leatherback turtle (Dermochelys coriacea), one of three genetically distinct stocks in the Indo‐Pacific region, has declined markedly during past decades. This metapopulation ...nests year‐round at beaches of several western Pacific island nations and has been documented through genetic analysis and telemetry studies to occur in multiple regions of the Pacific Ocean. To provide a large‐scale perspective of their movements, high‐use areas, and habitat associations, we report and synthesize results of 126 satellite telemetry deployments conducted on leatherbacks at western Pacific nesting beaches and at one eastern Pacific foraging ground during 2000–2007. A Bayesian switching state‐space model was applied to raw Argos‐acquired surface locations to estimate daily positions and behavioral mode (either transiting or area‐restricted search) for each turtle. Monthly areas of high use were identified for post‐nesting periods using kernel density estimation. There was a clear separation of migratory destinations for boreal summer vs. boreal winter nesters. Leatherbacks that nested during boreal summer moved into Large Marine Ecosystems (LMEs) of the temperate North Pacific Ocean or into tropical waters of the South China Sea. Turtles that nested during boreal winter moved into temperate and tropical LMEs of the southern hemisphere. Area‐restricted search occurred in temperate and tropical waters at diverse pelagic and coastal regions exhibiting a wide range of oceanographic features, including mesoscale eddies, coastal retention areas, current boundaries, or stationary fronts, all of which are known mechanisms for aggregating leatherback prey. Use of the most distant and temperate foraging ground, the California Current LME, required a 10–12 month trans‐Pacific migration and commonly involved multiple years of migrating between high‐latitude summer foraging grounds and low‐latitude eastern tropical Pacific wintering areas without returning to western Pacific nesting beaches. In contrast, tropical foraging destinations were reached within 5–7 months and appeared to support year‐round foraging, potentially allowing a more rapid return to nesting beaches. Based on these observations, we hypothesize that demographic differences are likely among nesting females using different LMEs of the Indo‐Pacific. The differences in movements and foraging strategies underscore the importance of and the need for ecosystem‐based management and coordinated Pacific‐wide conservation efforts.
Dietary methionine restriction (MR) is normally implemented using diets formulated from elemental amino acids (AA) that reduce methionine content to ∼0.17%. However, translational implementation of ...MR with elemental AA-based diets is intractable due to poor palatability. To solve this problem and restrict methionine using intact proteins, casein was subjected to mild oxidation to selectively reduce methionine. Diets were then formulated using oxidized casein, adding back methionine to produce a final concentration of 0.17%. The biological efficacy of dietary MR using the oxidized casein (Ox Cas) diet was compared with the standard elemental MR diet in terms of the behavioral, metabolic, endocrine, and transcriptional responses to the four diets. The Ox Cas MR diet faithfully reproduced the expected physiological, biochemical, and transcriptional responses in liver and inguinal white adipose tissue. Collectively, these findings demonstrate that dietary MR can be effectively implemented using casein after selective oxidative reduction of methionine.
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•Dietary methionine restriction improves biomarkers of metabolic health.•Elemental amino acid-based diets to restrict methionine are highly unpalatable.•Methionine has been depleted from casein by mild oxidation to solve low palatability.•Methionine restriction with oxidized casein is equally effective as elemental diet.
Metabolic engineering; Nutrition; Diet
Species distribution models have shown that blue whales (
) occur seasonally in high densities in the most biologically productive regions of the California Current Ecosystem (CCE). Satellite ...telemetry studies have additionally shown that blue whales in the CCE regularly switch between behavioral states consistent with area-restricted searching (ARS) and transiting, indicative of foraging in and moving among prey patches, respectively. However, the relationship between the environmental correlates that serve as a proxy of prey relative to blue whale movement behavior has not been quantitatively assessed.
We investigated the association between blue whale behavioral state and environmental predictors in the coastal environments of the CCE using a long-term satellite tracking data set (72 tagged whales; summer-fall months 1998-2008), and predicted the likelihood of ARS behavior at tracked locations using nonparametric multiplicative regression models. The models were built using data from years of cool, productive conditions and validated against years of warm, low-productivity conditions.
The best model contained four predictors: chlorophyll-
, sea surface temperature, and seafloor aspect and depth. This model estimated highest ARS likelihood (> 0.8) in areas with high chlorophyll-
levels (> 0.65 mg/m
), intermediate sea surface temperatures (11.6-17.5 °C), and shallow depths (< 850 m). Overall, the model correctly predicted behavioral state throughout the coastal environments of the CCE, while the validation indicated an ecosystem-wide reduction in ARS likelihood during warm years, especially in the southern portion. For comparison, a spatial coordinates model (longitude × latitude) performed slightly better than the environmental model during warm years, providing further evidence that blue whales exhibit strong foraging site fidelity, even when conditions are not conducive to successful foraging.
We showed that blue whale behavioral state in the CCE was predictable from environmental correlates and that ARS behavior was most prevalent in regions of known high whale density, likely reflecting where large prey aggregations consistently develop in summer-fall. Our models of whale movement behavior enhanced our understanding of species distribution by further indicating where foraging was more likely, which could be of value in the identification of key regions of importance for endangered species in management considerations. The models also provided evidence that decadal-scale environmental fluctuations can drive shifts in the distribution and foraging success of this blue whale population.
The rare phenomenon of nuclear wobbling motion has been investigated in the nucleus Au187. A longitudinal wobbling-bands pair has been identified and clearly distinguished from the associated ...signature-partner band on the basis of angular distribution measurements. Theoretical calculations in the framework of the particle rotor model are found to agree well with the experimental observations. This is the first experimental evidence for longitudinal wobbling bands where the expected signature partner band has also been identified, and establishes this exotic collective mode as a general phenomenon over the nuclear chart.
Trends in population abundance are often used to monitor species affected by human activities. For highly mobile species in dynamic environments, however, such as cetaceans in the marine realm, ...natural variability can confound attempts to detect and interpret trends in abundance. Environmental variability can cause dramatic shifts in the distribution of cetaceans, and thus abundance estimates for a fixed region may be based on a different proportion of the population each time. This adds variability, decreasing statistical power to detect trends and introducing uncertainty whether apparent trends represent true changes in population size or merely reflect natural changes in the distribution of cetaceans. To minimize these problems, surveys ideally would be based on species-specific design criteria that optimize sampling within all relevant habitat throughout a species' range. Our knowledge of cetacean habitats is limited, however, and financial and logistic constraints generally force those surveying cetacean abundance to include all species within a limited geographic region. Alternately, it may be possible to account for environmental variability analytically by including models of species-environment patterns in trend analyses, but this will be successful only if such models have interannual predictive power. I developed and evaluated generalized additive models of cetacean sighting rates in relation to environmental variables. I used data from shipboard surveys of Dall's porpoise (Phocoenoides dalli) and short-beaked common dolphins (Delphinus delphis) conducted in 1991, 1993, and 1996 off California. Sighting rates for these two species are variable and can be partially accounted for by environmental models, but additional surveys are needed to model species-environment relationships adequately. If patterns are consistent across years, generalized additive models may represent an effective tool for reducing uncertainty caused by environmental variability and for improving our ability to detect and interpret trends in abundance.
Dietary methionine restriction (MR) produces a rapid and persistent remodeling of white adipose tissue (WAT), an increase in energy expenditure (EE), and enhancement of insulin sensitivity. Recent ...work established that hepatic expression of FGF21 is robustly increased by MR.
mice were used to test whether FGF21 is an essential mediator of the physiological effects of dietary MR. The MR-induced increase in energy intake and EE and activation of thermogenesis in WAT and brown adipose tissue were lost in
mice. However, dietary MR produced a comparable reduction in body weight and adiposity in both genotypes because of a negative effect of MR on energy intake in
mice. Despite the similar loss in weight, dietary MR produced a more significant increase in in vivo insulin sensitivity in wild-type than in
mice, particularly in heart and inguinal WAT. In contrast, the ability of MR to regulate lipogenic and integrated stress response genes in liver was not compromised in
mice. Collectively, these findings illustrate that FGF21 is a critical mediator of the effects of dietary MR on EE, remodeling of WAT, and increased insulin sensitivity but not of its effects on hepatic gene expression.
The central North Pacific Ocean includes diverse temperate and tropical pelagic habitats. Studies of the abundance and distribution of cetaceans within these dynamic marine ecosystems have generally ...been patchy or conducted at coarse spatial and temporal scales, limiting their utility for pelagic conservation planning. Habitat-based density models provide a tool for identifying pelagic areas of importance to cetaceans, because model predictions are spatially explicit. In this study, we present habitat-based models of cetacean density that were developed and validated for the central North Pacific. Spatial predictions of cetacean densities and measures of uncertainty were derived based on data collected during 15 large-scale shipboard cetacean and ecosystem assessment surveys conducted from 1997 to 2012. We developed generalized additive models using static and remotely sensed dynamic habitat variables, including distance to land, sea-surface temperature (SST), standard deviation of SST, surface chlorophyll concentration, sea-surface height (SSH), and SSH root-mean-square variation. The resulting models, developed using new grid-based prediction methods, provide finer scale information on the distribution and density of cetaceans than previously available. Habitat-based abundance estimates around Hawaii are similar to those derived from standard line-transect analyses of the same data and provide enhanced spatial resolution to inform management and conservation of pelagic cetacean species.
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