76 research outputs found

    Ocean Surface Winds Drive Dynamics of Transoceanic Aerial Movements

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    Global wind patterns influence dispersal and migration processes of aerial organisms, propagules and particles, which ultimately could determine the dynamics of colonizations, invasions or spread of pathogens. However, studying how wind-mediated movements actually happen has been hampered so far by the lack of high resolution global wind data as well as the impossibility to track aerial movements. Using concurrent data on winds and actual pathways of a tracked seabird, here we show that oceanic winds define spatiotemporal pathways and barriers for large-scale aerial movements. We obtained wind data from NASA SeaWinds scatterometer to calculate wind cost (impedance) models reflecting the resistance to the aerial movement near the ocean surface. We also tracked the movements of a model organism, the Cory's shearwater (Calonectris diomedea), a pelagic bird known to perform long distance migrations. Cost models revealed that distant areas can be connected through “wind highways” that do not match the shortest great circle routes. Bird routes closely followed the low-cost “wind-highways” linking breeding and wintering areas. In addition, we found that a potential barrier, the near surface westerlies in the Atlantic sector of the Intertropical Convergence Zone (ITCZ), temporally hindered meridional trans-equatorial movements. Once the westerlies vanished, birds crossed the ITCZ to their winter quarters. This study provides a novel approach to investigate wind-mediated movements in oceanic environments and shows that large-scale migration and dispersal processes over the oceans can be largely driven by spatiotemporal wind patterns

    Ocean Surface Winds Drive Dynamics of Transoceanic Aerial Movements

    Get PDF
    Global wind patterns influence dispersal and migration processes of aerial organisms, propagules and particles, which ultimately could determine the dynamics of colonizations, invasions or spread of pathogens. However, studying how wind-mediated movements actually happen has been hampered so far by the lack of high resolution global wind data as well as the impossibility to track aerial movements. Using concurrent data on winds and actual pathways of a tracked seabird, here we show that oceanic winds define spatiotemporal pathways and barriers for large-scale aerial movements. We obtained wind data from NASA SeaWinds scatterometer to calculate wind cost (impedance) models reflecting the resistance to the aerial movement near the ocean surface. We also tracked the movements of a model organism, the Cory's shearwater (Calonectris diomedea), a pelagic bird known to perform long distance migrations. Cost models revealed that distant areas can be connected through “wind highways” that do not match the shortest great circle routes. Bird routes closely followed the low-cost “wind-highways” linking breeding and wintering areas. In addition, we found that a potential barrier, the near surface westerlies in the Atlantic sector of the Intertropical Convergence Zone (ITCZ), temporally hindered meridional trans-equatorial movements. Once the westerlies vanished, birds crossed the ITCZ to their winter quarters. This study provides a novel approach to investigate wind-mediated movements in oceanic environments and shows that large-scale migration and dispersal processes over the oceans can be largely driven by spatiotemporal wind patterns

    Ambient temperature does not affect fuelling rate in absence of digestive constraints in long-distance migrant shorebird fuelling up in captivity

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    Pre-flight fuelling rates in free-living red knots Calidris canutus, a specialized long-distance migrating shorebird species, are positively correlated with latitude and negatively with temperature. The single published hypothesis to explain these relationships is the heat load hypothesis that states that in warm climates red knots may overheat during fuelling. To limit endogenous heat production (measurable as basal metabolic rate BMR), birds would minimize the growth of digestive organs at a time they need. This hypothesis makes the implicit assumption that BMR is mainly driven by digestive organ size variation during pre-flight fuelling. To test the validity of this assumption, we fed captive knots with trout pellet food, a diet previously shown to quickly lead to atrophied digestive organs, during a fuelling episode. Birds were exposed to two thermal treatments (6 and 24°C) previously shown to generate different fuelling rates in knots. We made two predictions. First, easily digested trout pellet food rather than hard-shelled prey removes the heat contribution of the gut and would therefore eliminate an ambient temperature effect on fuelling rate. Second, if digestive organs were the main contributors to variations in BMR but did not change in size during fuelling, we would expect no or little change in BMR in birds fed ad libitum with trout pellets. We show that cold-acclimated birds maintained higher body mass and food intake (8 and 51%) than warm-acclimated birds. Air temperature had no effect on fuelling rate, timing of fuelling, timing of peak body mass or BMR. During fuelling, average body mass increased by 32% while average BMR increased by 15% at peak of mass and 26% by the end of the experiment. Our results show that the small digestive organs characteristic of a trout pellet diet did not prevent BMR from increasing during premigratory fuelling. Our results are not consistent with the heat load hypothesis as currently formulated

    An Introspective Comparison of Random Forest-Based Classifiers for the Analysis of Cluster-Correlated Data by Way of RF++

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    Many mass spectrometry-based studies, as well as other biological experiments produce cluster-correlated data. Failure to account for correlation among observations may result in a classification algorithm overfitting the training data and producing overoptimistic estimated error rates and may make subsequent classifications unreliable. Current common practice for dealing with replicated data is to average each subject replicate sample set, reducing the dataset size and incurring loss of information. In this manuscript we compare three approaches to dealing with cluster-correlated data: unmodified Breiman's Random Forest (URF), forest grown using subject-level averages (SLA), and RF++ with subject-level bootstrapping (SLB). RF++, a novel Random Forest-based algorithm implemented in C++, handles cluster-correlated data through a modification of the original resampling algorithm and accommodates subject-level classification. Subject-level bootstrapping is an alternative sampling method that obviates the need to average or otherwise reduce each set of replicates to a single independent sample. Our experiments show nearly identical median classification and variable selection accuracy for SLB forests and URF forests when applied to both simulated and real datasets. However, the run-time estimated error rate was severely underestimated for URF forests. Predictably, SLA forests were found to be more severely affected by the reduction in sample size which led to poorer classification and variable selection accuracy. Perhaps most importantly our results suggest that it is reasonable to utilize URF for the analysis of cluster-correlated data. Two caveats should be noted: first, correct classification error rates must be obtained using a separate test dataset, and second, an additional post-processing step is required to obtain subject-level classifications. RF++ is shown to be an effective alternative for classifying both clustered and non-clustered data. Source code and stand-alone compiled versions of command-line and easy-to-use graphical user interface (GUI) versions of RF++ for Windows and Linux as well as a user manual (Supplementary File S2) are available for download at: http://sourceforge.org/projects/rfpp/ under the GNU public license

    Discordant Gene Expression Signatures and Related Phenotypic Differences in Lamin A- and A/C-Related Hutchinson-Gilford Progeria Syndrome (HGPS)

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    Hutchinson-Gilford progeria syndrome (HGPS) is a genetic disorder displaying features reminiscent of premature senescence caused by germline mutations in the LMNA gene encoding lamin A and C, essential components of the nuclear lamina. By studying a family with homozygous LMNA mutation (K542N), we showed that HGPS can also be caused by mutations affecting both isoforms, lamin A and C. Here, we aimed to elucidate the molecular mechanisms underlying the pathogenesis in both, lamin A- (sporadic) and lamin A and C-related (hereditary) HGPS. For this, we performed detailed molecular studies on primary fibroblasts of hetero- and homozygous LMNA K542N mutation carriers, accompanied with clinical examinations related to the molecular findings. By assessing global gene expression we found substantial overlap in altered transcription profiles (13.7%; 90/657) in sporadic and hereditary HGPS, with 83.3% (75/90) concordant and 16.7% (15/90) discordant transcriptional changes. Among the concordant ones we observed down-regulation of TWIST2, whose inactivation in mice and humans leads to loss of subcutaneous fat and dermal appendages, and loss of expression in dermal fibroblasts and periadnexial cells from a LMNAK542N/K542N patient further confirming its pivotal role in skin development. Among the discordant transcriptional profiles we identified two key mediators of vascular calcification and bone metabolism, ENPP1 and OPG, which offer a molecular explanation for the major phenotypic differences in vascular and bone disease in sporadic and hereditary HGPS. Finally, this study correlates reduced TWIST2 and OPG expression with increased osteocalcin levels, thereby linking altered bone remodeling to energy homeostasis in hereditary HGPS

    Fastloc-GPS reveals daytime departure and arrival during long-distance migration and the use of different resting strategies in sea turtles

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    Determining the time of day that animals initiate and end migration, as well as variation in diel movement patterns during migration, provides insights into the types of strategy used to maximise energy efficiency and ensure successful completion of migration. However, obtaining this level of detail has been difficult for long-distance migratory marine species. Thus, we investigated whether the large volume of highly accurate locations obtained by Argos-linked Fastloc-GPS transmitters could be used to identify the time of day that adult green (n = 8 turtles, 9487 locations) and loggerhead (n = 46 turtles, 47,588 locations) sea turtles initiate and end migration, along with potential resting strategies during migration. We found that departure from and arrival at breeding, stopover and foraging sites consistently occurred during the daytime, which is consistent with previous findings suggesting that turtles might use solar visual cues for orientation. Only seven turtles made stopovers (of up to 6 days and all located close to the start or end of migration) during migration, possibly to rest and/or refuel; however, observations of day versus night speed of travel indicated that turtles might use other mechanisms to rest. For instance, turtles travelled 31% slower at night compared to day during their oceanic crossings. Furthermore, within the first 24 h of entering waters shallower than 100 m towards the end of migration, some individuals travelled 72% slower at night, repeating this behaviour intermittently (each time for a one-night duration at 3–6 day intervals) until reaching the foraging grounds. Thus, access to data-rich, highly accurate Argos-linked Fastloc-GPS provided information about differences in day versus night activity at different stages in migration, allowing us, for the first time, to compare the strategies used by a marine vertebrate with terrestrial land-based and flying species
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