900 resultados para Bird ringing
Gene loss, adaptive evolution and the co-evolution of plumage coloration genes with opsins in birds.
Resumo:
BACKGROUND: The wide range of complex photic systems observed in birds exemplifies one of their key evolutionary adaptions, a well-developed visual system. However, genomic approaches have yet to be used to disentangle the evolutionary mechanisms that govern evolution of avian visual systems. RESULTS: We performed comparative genomic analyses across 48 avian genomes that span extant bird phylogenetic diversity to assess evolutionary changes in the 17 representatives of the opsin gene family and five plumage coloration genes. Our analyses suggest modern birds have maintained a repertoire of up to 15 opsins. Synteny analyses indicate that PARA and PARIE pineal opsins were lost, probably in conjunction with the degeneration of the parietal organ. Eleven of the 15 avian opsins evolved in a non-neutral pattern, confirming the adaptive importance of vision in birds. Visual conopsins sw1, sw2 and lw evolved under negative selection, while the dim-light RH1 photopigment diversified. The evolutionary patterns of sw1 and of violet/ultraviolet sensitivity in birds suggest that avian ancestors had violet-sensitive vision. Additionally, we demonstrate an adaptive association between the RH2 opsin and the MC1R plumage color gene, suggesting that plumage coloration has been photic mediated. At the intra-avian level we observed some unique adaptive patterns. For example, barn owl showed early signs of pseudogenization in RH2, perhaps in response to nocturnal behavior, and penguins had amino acid deletions in RH2 sites responsible for the red shift and retinal binding. These patterns in the barn owl and penguins were convergent with adaptive strategies in nocturnal and aquatic mammals, respectively. CONCLUSIONS: We conclude that birds have evolved diverse opsin adaptations through gene loss, adaptive selection and coevolution with plumage coloration, and that differentiated selective patterns at the species level suggest novel photic pressures to influence evolutionary patterns of more-recent lineages.
Resumo:
BACKGROUND: Parrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learning birds. They can imitate human speech, synchronize their body movements to a rhythmic beat, and understand complex concepts of referential meaning to sounds. However, little is known about the genetics of these traits. Elucidating the genetic bases would require whole genome sequencing and a robust assembly of a parrot genome. FINDINGS: We present a genomic resource for the budgerigar, an Australian Parakeet (Melopsittacus undulatus) -- the most widely studied parrot species in neuroscience and behavior. We present genomic sequence data that includes over 300× raw read coverage from multiple sequencing technologies and chromosome optical maps from a single male animal. The reads and optical maps were used to create three hybrid assemblies representing some of the largest genomic scaffolds to date for a bird; two of which were annotated based on similarities to reference sets of non-redundant human, zebra finch and chicken proteins, and budgerigar transcriptome sequence assemblies. The sequence reads for this project were in part generated and used for both the Assemblathon 2 competition and the first de novo assembly of a giga-scale vertebrate genome utilizing PacBio single-molecule sequencing. CONCLUSIONS: Across several quality metrics, these budgerigar assemblies are comparable to or better than the chicken and zebra finch genome assemblies built from traditional Sanger sequencing reads, and are sufficient to analyze regions that are difficult to sequence and assemble, including those not yet assembled in prior bird genomes, and promoter regions of genes differentially regulated in vocal learning brain regions. This work provides valuable data and material for genome technology development and for investigating the genomics of complex behavioral traits.
Resumo:
Mitchell et al. argue that divergence-time estimates for our avian phylogeny were too young because of an "inappropriate" maximum age constraint for the most recent common ancestor of modern birds and that, as a result, most modern bird orders diverged before the Cretaceous-Paleogene mass extinction event 66 million years ago instead of after. However, their interpretations of the fossil record and timetrees are incorrect.
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To provide context for the diversification of archosaurs--the group that includes crocodilians, dinosaurs, and birds--we generated draft genomes of three crocodilians: Alligator mississippiensis (the American alligator), Crocodylus porosus (the saltwater crocodile), and Gavialis gangeticus (the Indian gharial). We observed an exceptionally slow rate of genome evolution within crocodilians at all levels, including nucleotide substitutions, indels, transposable element content and movement, gene family evolution, and chromosomal synteny. When placed within the context of related taxa including birds and turtles, this suggests that the common ancestor of all of these taxa also exhibited slow genome evolution and that the comparatively rapid evolution is derived in birds. The data also provided the opportunity to analyze heterozygosity in crocodilians, which indicates a likely reduction in population size for all three taxa through the Pleistocene. Finally, these data combined with newly published bird genomes allowed us to reconstruct the partial genome of the common ancestor of archosaurs, thereby providing a tool to investigate the genetic starting material of crocodilians, birds, and dinosaurs.
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The consecutive, partly overlapping emergence of expert systems and then neural computation methods among intelligent technologies, is reflected in the evolving scene of their application to nuclear engineering. This paper provides a bird's eye view of the state of the application in the domain, along with a review of a particular task, the one perhaps economically more important: refueling design in nuclear power reactors.
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This report provides an overview of water and sediment quality within the Mersey Estuary European Marine Site (EMS) and examines evidence for their influence on bioloigcal condition. It has not been possible to determine adequately whether prevailing conditions in the Mersey impact on the interest features of the site as studies which address this issue have not been carried out. It is only possible to review the current level of knowledge regarding the biological and chemical status for the estuary, and extrapolate risks to the bird population. Often information relates to sites outside the EMS; where this is the case the authors have tried to appraise the general status of the estuary, based on best available knowledge.
Resumo:
1. Abundant mid-trophic pelagic fish often play a central role in marine ecosystems, both as links between zooplankton and top predators and as important fishery targets. In the North Sea, the lesser sandeel occupies this position, being the main prey of many bird, mammal and fish predators and the target of a major industrial fishery. However, since 2003, sandeel landings have decreased by > 50%, and many sandeel-dependent seabirds experienced breeding failures in 2004. 2. Despite the major economic implications, current understanding of the regulation of key constituents of this ecosystem is poor. Sandeel abundance may be regulated 'bottom-up' by food abundance, often thought to be under climatic control, or 'top-down' by natural or fishery predation. We tested predictions from these two hypotheses by combining unique long-term data sets (1973–2003) on seabird breeding productivity from the Isle of May, SE Scotland, and plankton and fish larvae from the Continuous Plankton Recorder survey. We also tested whether seabird breeding productivity was more tightly linked to sandeel biomass or quality (size) of individual fish. 3. The biomass of larval sandeels increased two- to threefold over the study period and was positively associated with proxies of the abundance of their plankton prey. Breeding productivity of four seabirds bringing multiple prey items to their offspring was positively related to sandeel larval biomass with a 1-year lag, indicating dependence on 1-year-old fish, but in one species bringing individual fish it was strongly associated with the size of adult sandeels. 4. These links are consistent with bottom-up ecosystem regulation and, with evidence from previous studies, indicate how climate-driven changes in plankton communities can affect top predators and potentially human fisheries through the dynamics of key mid-trophic fish. However, the failing recruitment to adult sandeel stocks and the exceptionally low seabird breeding productivity in 2004 were not associated with low sandeel larval biomass in 2003, so other mechanisms (e.g. predation, lack of suitable food after metamorphosis) must have been important in this case. Understanding ecosystem regulation is extremely important for predicting the fate of keystone species, such as sandeels, and their predators.
Resumo:
1. A first step in the analysis of complex movement data often involves discretisation of the path into a series of step-lengths and turns, for example in the analysis of specialised random walks, such as Lévy flights. However, the identification of turning points, and therefore step-lengths, in a tortuous path is dependent on ad-hoc parameter choices. Consequently, studies testing for movement patterns in these data, such as Lévy flights, have generated debate. However, studies focusing on one-dimensional (1D) data, as in the vertical displacements of marine pelagic predators, where turning points can be identified unambiguously have provided strong support for Lévy flight movement patterns. 2. Here, we investigate how step-length distributions in 3D movement patterns would be interpreted by tags recording in 1D (i.e. depth) and demonstrate the dimensional symmetry previously shown mathematically for Lévy-flight movements. We test the veracity of this symmetry by simulating several measurement errors common in empirical datasets and find Lévy patterns and exponents to be robust to low-quality movement data. 3. We then consider exponential and composite Brownian random walks and show that these also project into 1D with sufficient symmetry to be clearly identifiable as such. 4. By extending the symmetry paradigm, we propose a new methodology for step-length identification in 2D or 3D movement data. The methodology is successfully demonstrated in a re-analysis of wandering albatross Global Positioning System (GPS) location data previously analysed using a complex methodology to determine bird-landing locations as turning points in a Lévy walk. For this high-resolution GPS data, we show that there is strong evidence for albatross foraging patterns approximated by truncated Lévy flights spanning over 3·5 orders of magnitude. 5. Our simple methodology and freely available software can be used with any 2D or 3D movement data at any scale or resolution and are robust to common empirical measurement errors. The method should find wide applicability in the field of movement ecology spanning the study of motile cells to humans.
Resumo:
Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.
Resumo:
Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.