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Flight costs are predicted to vary with environmental conditions, and this should ultimately determine the movement capacity and distributions of large soaring birds. Despite this, little is known about how flight effort varies with environmental parameters. We deployed bio-logging devices on the world’s heaviest soaring bird, the Andean condor (Vultur gryphus), to assess the extent to which these birds can operate without resorting to powered flight. Our records of individual wingbeats in >216 h of flight show that condors can sustain soaring across a wide range of wind and thermal conditions, flapping for only 1% of their flight time. This is among the very lowest estimated movement costs in vertebrates. One bird even flew for >5 h without flapping, covering ∼172 km. Overall, > 75% of flapping flight was associated with takeoffs. Movement between weak thermal updrafts at the start of the day also imposed a metabolic cost, with birds flapping toward the end of glides to reach ephemeral thermal updrafts. Nonetheless, the investment required was still remarkably low, and even in winter conditions with weak thermals, condors are only predicted to flap for ∼2 s per kilometer. Therefore, the overall flight effort in the largest soaring birds appears to be constrained by the requirements for takeoff.

During January-September 2024, a national active case-finding program in Peru's prisons screened >38,000 persons for tuberculosis (TB) using chest radiography with automated interpretation and rapid molecular tests. The program found high percentages of TB, rifampin-resistant TB, and asymptomatic infections, demonstrating the urgent need for systematic screening among incarcerated populations.

Sexual segregation is widely reported among sexually dimorphic species and generally attributed to intraspecific competition. Prey diversity and human activities can reinforce niche segregation by increasing resource heterogeneity. Here, we explored trophic and spatial sexual segregation in the only avian scavenger that exhibits pronounced sexual size dimorphism (up to 50% difference in body mass) and a highly despotic social system, the Andean condor (Vultur gryphus). We predicted that larger and dominant males would exclude smaller and subordinate females from high-quality resources, leading to sexual segregation particularly in human-dominated landscapes showing increased prey diversity. We compared resource use between females and males across six sites in Argentina featuring a range of prey diversity via stable isotopes analysis of molted feathers (n = 141 individuals). We then focused on two sites featuring contrasting levels of prey diversity and quantified assimilated diet via stable isotopes and space use via GPS monitoring (n = 23 and 12 tagged individuals). We found no clear differences in isotopic niche space, individual variation in isotopic signature, or assimilated diet between females and males. However, there were differences in foraging locations between sexes, with females apparently using areas of fewer food resources more frequently than males. Local conditions defined the dynamics of fine-scale sexual differences in foraging sites; yet, unpredictable and ephemeral carrion resources likely prevent segregation by sexes at the landscape scale. Our study highlights complex dynamics of sexual segregation in vultures and the relevancy of analyses under multiple spatial–temporal scales to explore segregation in social species.

Real-valued functions of complex arguments violate the Cauchy-Riemann conditions and, consequently, do not have Taylor series expansion. Therefore, optimization methods based on derivatives cannot be directly applied to this class of functions. This is circumvented by mapping the problem to the field of the real numbers by considering real and imaginary parts of the complex arguments as the new independent variables. We introduce a stochastic optimization method that works within the field of the complex numbers. This has two advantages: Equations on complex arguments are simpler and easy to analyze and the use of the complex structure leads to performance improvements. The method produces a sequence of estimates that converges asymptotically in mean to the optimizer. Each estimate is generated by evaluating the target function at two different randomly chosen points. Thereby, the method allows the optimization of functions with unknown parameters. Furthermore, the method exhibits a large performance enhancement. This is demonstrated by comparing its performance with other algorithms in the case of quantum tomography of pure states. The method provides solutions which can be two orders of magnitude closer to the true minima or achieve similar results as other methods but with three orders of magnitude less resources.

Telemetry-based movement research has become central for learning about the behavior, ecology and conservation of wide-ranging species. Particularly, early telemetry studies were conducted on vultures and condors due to three main reasons: i) these birds capture the curiosity of humans, ii) their large body size allows researchers to deploy large telemetry units, and iii) they are of high conservation concern. This has resulted in a great number of scientific articles that remain scattered throughout the literature. To achieve a more cohesive view of vultures and condors movement behavior, we review all telemetry studies published up to 2017. We first present a descriptive summary of the technical and design characteristics of these studies (e.g. target species, tagging location, number of individuals tagged) and go on to discuss them under a common conceptual framework; the Movement Ecology Paradigm. The articles found ( N  = 97) were mainly published in the last decade and based on the tagging of individuals from 14 species (61% of the extant species) and 24 countries. Foraging was the most in-depth investigated movement phase (25 studies), with studies covering several species, using both phenomenological and mechanistic approaches and tackling the role of different drivers of movement. In contrast, commuting and natal dispersal phases were only superficially investigated (3 and 8 studies, respectively). Finally, studies dealing with the conservation and management also comprised a large portion of the reviewed articles (24 studies). Telemetry studies have revealed relevant details of vultures and condors movements, with highly accurate measurements of flight energetics and a better understanding of the morphological, physiological and context-dependent drivers that underlie the movement decisions of these birds. However, we also detected several information gaps. We expect this review helps researchers to focus their efforts and funds where more information is needed.

Context Understanding how animals respond to the energy landscape is crucial for elucidating the mechanisms of habitat selection, movement strategies, and connectivity dynamics. However, assessing the responses of highly mobile and long-lived species is challenging, as movement behaviors related to distinct life-history requirements may operate at extreme spatial and temporal scales. Objectives We combined movement and genetic data to investigate how energy landscape features influence ecologically and evolutionarily relevant dispersal patterns in an extreme soaring specialist, the Andean condor ( Vultur gryphus ). Methods We analyzed GPS data via Resource Selection Functions and conducted Landscape Genetic models for Andean condors from southern South America, considering static and dynamic landscape features. Connectivity models were used to identify conservation priority areas by integrating behavioral states critical for ecological (encamped and exploratory movements) and evolutionary processes (gene-flow). Results Topographic features emerged as key determinants of gene-flow patterns, while climatic variables were crucial for exploratory and encamped flights. Condors increased space use and connectivity during summer. While Resource Selection Function failed to predict gene-flow routes via path-based analysis, landscape-wide approaches identified connectivity barriers in flat terrain with poor uplift conditions for soaring. Conclusions Our study revealed the critical role of the energy landscape and life-history requirements in shaping habitat selection and population connectivity in Andean condors. The distinct, yet complementary patterns of habitat usage across various flight behaviors highlight the nuanced and complex use of the landscape. These findings highlight how variation in movement behaviors affects connectivity planning, urging conservation studies to incorporate movement-mode distinctions.

Context Widespread globally, roads impact the distribution of wildlife by influencing habitat use and avoidance patterns near roadways and disrupting movement across them. Wildlife responses to roads are known to vary across species; however within species, the response to roads may depend on the season or the individual’s behavioral state. Objectives We assess the movement behavior and space use of the most widespread large herbivore in Patagonia, the guanaco ( Lama guanicoe). We estimated the preference or avoidance to paved or unpaved roads (the proximity effect) and the preference or avoidance to traverse them (the crossing effect). Methods Using GPS collar data, we combined Hidden Markov Models with an integrated step selection analysis to segment guanaco movement trajectories into individual behaviors and test for differences in road effects on movement. Results We found that guanacos display distinct movement responses to different types of roads depending on their behavioral state. Guanacos select for proximity to paved roads while foraging, but against them when traveling. Yet, guanacos select for unpaved roads when traveling. Despite the selection for proximity to paved roads, guanacos avoid crossing them, irrespective of their behavioral state. Conclusion Our findings offer significant implications for guanaco distribution and management across Patagonia. The selection for roads strongly influences the distribution of guanacos, which could concentrate grazing in some areas while freeing others. Despite potential benefits such as increased vegetation near roadsides, increased association with roads while foraging may result in an ecological trap. Finally, the strong aversion to crossing paved roads raises concerns about habitat loss and connectivity.

The main aim of this study was to generate an adequate sub-phenotypic clustering model of class III skeletal malocclusion in an adult population of southern European origin. The study design was conducted in two phases, a preliminary cross-sectional study and a subsequent discriminatory evaluation by main component and cluster analysis to identify differentiated skeletal sub-groups with differentiated phenotypic characteristics. Radiometric data from 699 adult patients of southern European origin were analyzed in 212 selected subjects affected by class III skeletal malocclusion. The varimax rotation was used with Kaiser normalization, to prevent variables with more explanatory capacity from affecting the rotation. A total of 21,624 radiographic measurements were obtained as part of the cluster model generation, using a total set of 55 skeletal variables for the subsequent analysis of the major component and cluster analyses. Ten main axes were generated representing 92.7% of the total variation. Three main components represented 58.5%, with particular sagittal and vertical variables acting as major descriptors. Post hoc phenotypic clustering retrieved six clusters: C1:9.9%, C2:18.9%, C3:33%, C4:3.77%, C5:16%, and C6:16%. In conclusion, phenotypic variation was found in the southern European skeletal class III population, demonstrating the existence of phenotypic variations between identified clusters in different ethnic groups.

Genome-wide association studies (GWAS) have successfully identified several risk loci for Alzheimer's disease (AD). Nonetheless, these loci do not explain the entire susceptibility of the disease, suggesting that other genetic contributions remain to be identified. Here, we performed a meta-analysis combining data of 4,569 individuals (2,540 cases and 2,029 healthy controls) derived from three publicly available GWAS in AD and replicated a broad genomic region (>248,000 bp) associated with the disease near the APOE/TOMM40 locus in chromosome 19. To detect minor effect size contributions that could help to explain the remaining genetic risk, we conducted network-based pathway analyses either by extracting gene-wise p-values (GW), defined as the single strongest association signal within a gene, or calculated a more stringent gene-based association p-value using the extended Simes (GATES) procedure. Comparison of these strategies revealed that ontological sub-networks (SNs) involved in glutamate signaling were significantly overrepresented in AD (p<2.7×10(-11), p<1.9×10(-11); GW and GATES, respectively). Notably, glutamate signaling SNs were also found to be significantly overrepresented (p<5.1×10(-8)) in the Alzheimer's disease Neuroimaging Initiative (ADNI) study, which was used as a targeted replication sample. Interestingly, components of the glutamate signaling SNs are coordinately expressed in disease-related tissues, which are tightly related to known pathological hallmarks of AD. Our findings suggest that genetic variation within glutamate signaling contributes to the remaining genetic risk of AD and support the notion that functional biological networks should be targeted in future therapies aimed to prevent or treat this devastating neurological disorder.