Abundance, distribution, and habitat of leatherback turtles (Dermochelys coriacea) off California, 1990−2003

Leatherback turtles (Dermochelys coriacea) are regularly seen off the U.S. West Coast, where they forage on jellyfish (Scyphomedusae) during summer and fall. Aerial line-transect surveys were conducted in neritic waters (<92 m depth) off central and northern California during 1990−2003, providing the first foraging population estimates for Pacific leatherback turtles. Males and females of about 1.1 to 2.1 m length were observed. Estimated abundance was linked to the Northern Oscillation Index and ranged from 12 (coefficient of variation [CV] =0.75) in 1995 to 379 (CV= 0.23) in 1990, averaging 178 (CV= 0.15). Greatest densities were found off central California, where oceanographic retention areas or upwelling shadows created favorable habitat for leatherback turtle prey. Results from independent telemetry studies have linked leatherback turtles off the U.S. West Coast to one of the two largest remaining Pacific breeding populations, at Jamursba Medi, Indonesia. Nearshore waters off California thus represent an important foraging region for the critically endangered Pacific leatherback turtle

Barium abundance in red giants of NGC 6752. Non-local thermodynamic equilibrium and three-dimensional effects

(Abridged) Aims: We study the effects related to departures from non-local thermodynamic equilibrium (NLTE) and homogeneity in the atmospheres of red giant stars in Galactic globular cluster NGC 6752, to assess their influence on the formation of Ba II lines. Methods: One-dimensional (1D) local thermodynamic equilibrium (LTE) and 1D NLTE barium abundances were derived using classical 1D ATLAS stellar model atmospheres. The three-dimensional (3D) LTE abundances were obtained for 8 red giants on the lower RGB, by adjusting their 1D LTE abundances using 3D-1D abundance corrections, i.e., the differences between the abundances obtained from the same spectral line using the 3D hydrodynamical (CO5BOLD) and classical 1D (LHD) stellar model atmospheres. Results: The mean 1D barium-to-iron abundance ratios derived for 20 giants are _{1D NLTE} = 0.05 \pm0.06 (stat.) \pm0.08 (sys.). The 3D-1D abundance correction obtained for 8 giants is small (~+0.05 dex), thus leads to only minor adjustment when applied to the mean 1D NLTE barium-to-iron abundance ratio for the 20 giants, _{3D+NLTE} = 0.10 \pm0.06(stat.) \pm0.10(sys.). The intrinsic abundance spread between the individual cluster stars is small and can be explained in terms of uncertainties in the abundance determinations. Conclusions: Deviations from LTE play an important role in the formation of barium lines in the atmospheres of red giants studied here. The role of 3D hydrodynamical effects should not be dismissed either, even if the obtained 3D-1D abundance corrections are small. This result is a consequence of subtle fine-tuning of individual contributions from horizontal temperature fluctuations and differences between the average temperature profiles in the 3D and 1D model atmospheres: owing to the comparable size and opposite sign, their contributions nearly cancel each other.Comment: Minor typos corrected. Accepted for publication in A&A (9 pages, 3 figures, 6 tables

A long-term decline in the abundance of endangered leatherback turtles, \u3cem\u3eDermochelys coriacea\u3c/em\u3e, at a foraging ground in the California Current Ecosystem

Pacific leatherback turtles (Dermochelys coriacea) are critically endangered, and declines have been documented at multiple nesting sites throughout the Pacific. The western Pacific leatherback forages in temperate and tropical waters of the Indo-Pacific region, and about 38–57% of summer-nesting females from the largest remaining nesting population in Papua Barat (Indonesia) migrate to distant foraging grounds off the U.S. West Coast, including neritic waters off central California. In this study, we examined the trend in leatherback abundance off central California from 28 years of aerial survey data from coast-wide and adaptive fine-scale surveys. We used a Bayesian hierarchical analysis framework, including a process model of leatherback population density and an observation model relating leatherback observations to distance sampling methods. We also used time-depth data from biologgers deployed on 21 foraging leatherback turtles in the study area to account for detection biases associated with diving animals. Our results indicate that leatherback abundance has declined at an annual rate of −5.6% (95% credible interval −9.8% to −1.5%), without any marked changes in ocean conditions or prey availability. These results are similar to the nesting population trends of −5.9% and −6.1% per year estimated at Indonesian index beaches, which comprise 75% of western Pacific nesting activity. Combined, the declining trends underscore the need for coordinated international conservation efforts and long-term population monitoring to avoid extirpation of western Pacific leatherback turtles

Performance Evaluation of Cetacean Species Distribution Models Developed Using Generalized Additive Models and Boosted Regression Trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

VLT/UVES Spectroscopy of Individual Stars in Three Globular Clusters in the Fornax Dwarf Spheroidal Galaxy

We present a high resolution (R ~ 43000) abundance analysis of a total of nine stars in three of the five globular clusters associated with the nearby Fornax dwarf spheroidal galaxy. These three clusters (1, 2 and 3) trace the oldest, most metal-poor stellar populations in Fornax. We determine abundances of O, Mg, Ca, Ti, Cr, Mn, Fe, Ni, Zn, Y, Ba, La, Nd and Eu in most of these stars, and for some stars also Mn and La. We demonstrate that classical indirect methods (isochrone fitting and integrated spectra) of metallicity determination lead to values of [Fe/H] which are 0.3 to 0.5 dex too high, and that this is primarily due to the underlying reference calibration typically used by these studies. We show that Cluster 1, with [Fe /H] = -2.5, now holds the record for the lowest metallicity globular cluster. We also measure an over-abundance of Eu in Cluster 3 stars that has only been previously detected in a subgroup of stars in M15. We find that the Fornax globular cluster properties are a global match to what is found in their Galactic counterparts; including deep mixing abundance patterns in two stars. We conclude that at the epoch of formation of globular clusters both the Milky Way and the Fornax dwarf spheroidal galaxy shared the same initial conditions, presumably pre-enriched by the same processes, with identical nucleosynthesis patterns.Comment: 16 pages, 12 figures. Accepted for publication in A&

Multiple populations in globular clusters. Lessons learned from the Milky Way globular clusters

Recent progress in studies of globular clusters has shown that they are not simple stellar populations, being rather made of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is then arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second parameter problem, it also opens new perspectives about the relation between globular clusters and the halo of our Galaxy, and by extension of all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focusing on the most recent studies. Several points remain to be properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.Comment: In press (The Astronomy and Astrophysics Review

The lithium content of the globular cluster NGC 6397

We make use of high resolution, high signal-to-noise ratio spectra of 12 turn-off stars in the metal-poor globular cluster NGC 6397 to measure its lithium content. We conclude that they all have the same lithium abundance A(Li) = 2.34 with a standard deviation of 0.056 dex. We use this result, together with Monte Carlo simulations, to estimate that the maximum allowed intrinsic scatter is of the order of 0.035 dex. This is a new stringent constraint to be fulfilled by stellar models which predict Li depletion. We argue that although a mild depletion of 0.1 -- 0.2 dex, as predicted by recent models, cannot be ruled out, there is no compelling reason for it. This fact, together with the good agreement with the Li abundance observed in field stars, supports the primordial origin of lithium in metal-poor stars. Taking the above value as the primordial lithium abundance implies a cosmic baryonic density which is either Omega_b h^2 = 0.016 +/- 0.004 or Omega_b h^2 = 0.005 ^{+0.0026}_{-0.0006}, from the predictions of standard big bang nucleosynthesis. The high baryonic density solution is in agreement with recent results on the primordial abundance of deuterium and 3He and on the estimates derived from the fluctuations of the cosmic microwave background.Comment: A&A, accepte

First Stars VIII -- Enrichment of the neutron-capture elements in the early Galaxy

Our aim is to measure accurate, homogeneous neutron-capture element abundances for the sample of 32 EMP giant stars studied earlier in this series, including 22 stars with [Fe/H] $< -$3.0. Based on high-resolution, high S/N spectra from the ESO VLT/UVES, 1D, LTE model atmospheres, and synthetic spectrum fits, we determine abundances or upper limits for the 16 elements Sr, Y, Zr, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm, and Yb in all stars. As found earlier, [Sr/Fe], [Y/Fe], [Zr/Fe] and [Ba/Fe] are below Solar in the EMP stars, with very large scatter. However, we find a tight anti-correlation of [Sr/Ba], [Y/Ba], and [Zr/Ba] with [Ba/H] for $-4.5 <$ [Ba/H] $< -2.5$, also when subtracting the contribution of the main $r$-process as measured by [Ba/H]. The huge, well-characterised scatter of the [n-capture/Fe] ratios in our EMP stars is in stark contrast to the negligible dispersion in the [$\alpha$/Fe] and [Fe-peak/Fe] ratios for the same stars found in Paper V. These results demonstrate that a second (``weak'' or LEPP) $r$-process dominates the production of the lighter neutron-capture elements for [Ba/H] $< -2.5$. The combination of very consistent [$\alpha$/Fe] and erratic [n-capture/Fe] ratios indicates that inhomogeneous models for the early evolution of the halo are needed. Our accurate data provide strong constraints on future models of the production and mixing of the heavy elements in the early Galaxy.Comment: 19 pages, 16 figures, A&A accepte

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group