A decade of movement ecology

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. Recent advances in tracking technology have enabled fundamental questions about movement to be tackled, leading to the development of the movement ecology framework (MEF), considered a milestone in the field [1]. The MEF introduced an integrative theory of organismal movement, linking internal state, motion capacity and navigation capacity to external factors. Here, a decade later, we investigated the current state of research in the field. Using a text mining approach on >8000 peer-reviewed papers in movement ecology, we explored the main research topics, evaluated the impact of the MEF, and assessed changes in the use of technological devices, software and statistical methods. The number of publications has increased considerably and there have been major technological changes in the past decade (i.e.~increased use of GPS devices, accelerometers and video cameras, and a convergence towards R), yet we found that research focuses on the same questions, specifically, on the effect of environmental factors on movement and behavior. In practice, it appears that movement ecology research does not reflect the MEF. We call on researchers to transform the field from technology-driven to embrace interdisciplinary collaboration, in order to reveal key processes underlying movement (e.g.~navigation), as well as evolutionary, physiological and life-history consequences of particular strategies

Analysis of Movement Recursions to Detect Reproductive Events and Estimate Their Fate in Central Place Foragers

Background Recursive movement patterns have been used to detect behavioral structure within individual movement trajectories in the context of foraging ecology, home-ranging behavior, and predator avoidance. Some animals exhibit movement recursions to locations that are tied to reproductive functions, including nests and dens; while existing literature recognizes that, no method is currently available to explicitly target different types of revisited locations. Moreover, the temporal persistence of recursive movements to a breeding location can carry information regarding the fate of breeding attempts, but it has never been used as a metric to quantify recursive movement patterns. Here, we introduce a method to locate breeding attempts and estimate their fate from GPS-tracking data of central place foragers. We tested the performance of our method in three bird species differing in breeding ecology (wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus)) and implemented it in the R package ‘nestR’. Methods We identified breeding sites based on the analysis of recursive movements within individual tracks. Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls. We then estimated individual nest survival as a binary measure of reproductive fate (success, corresponding to fledging of at least one chick, or failure) from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable revisitation patterns, probability of visit detection, and missing data. Results Across the three species, positive predictive value of the nest-site detection algorithm varied between 87 and 100% and sensitivity between 88 and 92%, and we correctly estimated the fate of 86–100% breeding attempts. Conclusions By providing a method to formally distinguish among revisited locations that serve different ecological functions and introducing a probabilistic framework to quantify temporal persistence of movement recursions, we demonstrated how the analysis of recursive movement patterns can be applied to estimate reproduction in central place foragers. Beyond avian species, the principles of our method can be applied to other central place foraging breeders such as denning mammals. Our method estimates a component of individual fitness from movement data and will help bridge the gap between movement behavior, environmental factors, and their fitness consequences

Navigating through the r packages for movement

Case No. 900052-CA Category No. 14b APPEAL FROM AN ORDER OF SUMMARY JUDGMENT AND DISMISSAL OF COMPLAINT WITH PREJUDICE OF THE SECOND JUDICIAL DISTRICT COURT FOR DAVIS COUNTY, STATE OF UTAH JUDGE DOUGLAS L. CORNABY REPLY BRIEF OF APPELLANT

Linking Animals Aloft with the Terrestrial Landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals

Linking Animals Aloft with the Terrestrial Landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals

PCORnet Antibiotics and Childhood Growth Study: Process for Cohort Creation and Cohort Description

OBJECTIVES: The National Patient-Centered Clinical Research Network (PCORnet) supports observational and clinical research using health care data. The PCORnet Antibiotics and Childhood Growth Study is one of PCORnet’s inaugural observational studies. We sought to describe the processes used to integrate and analyze data from children across 35 participating institutions, the cohort characteristics, and prevalence of antibiotic use. METHODS:We included children in the cohort if they had at least one same-day height and weight measured in each of 3 age periods: 1) before 12 months, 2) 12 to 30 months, and 3) after 24 months. We distributed statistical queries that each institution ran on its local version of the PCORnet Common Data Model, with aggregate data returned for analysis. We defined overweight or obesity as age- and sex-specific body mass index ≥85th percentile, obesity ≥95th percentile, and severe obesity ≥120% of the 95th percentile. RESULTS: A total of 681,739 children met the cohort inclusion criteria, and participants were racially/ethnically diverse (24.9% black, 17.5% Hispanic). Before 24 months of age, 55.2% of children received at least one antibiotic prescription; 21.3% received a single antibiotic prescription; 14.3% received 4 or more; and 33.3% received a broad-spectrum antibiotic. Overweight and obesity prevalence was 27.6% at age 4 to(n = 362,044) and 36.2% at 9 to(n = 58,344). CONCLUSIONS: The PCORnet Antibiotics and Childhood Growth Study is a large national longitudinal observational study in a diverse population that will examine the relationship between early antibiotic use and subsequent growth patterns in children

Recent trends in movement ecology of animals and human mobility

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. In 2008, the movement ecology framework (MEF Nathan et al. in PNAS 105(49):19052–19059, 2008) introduced an integrative theory of organismal movement—linking internal state, motion capacity, and navigation capacity to external factors—which has been recognized as a milestone in the field. Since then, the study of movement experienced a technological boom, which provided massive quantities of tracking data of both animal and human movement globally and at ever finer spatio-temporal resolutions. In this work, we provide a quantitative assessment of the state of research within the MEF, focusing on animal movement, including humans and invertebrates, and excluding movement of plants and microorganisms. Using a text mining approach, we digitally scanned the contents of [Formula: see text] papers from 2009 to 2018 available online, identified tools and methods used, and assessed linkages between all components of the MEF. Over the past decade, the publication rate has increased considerably, along with major technological changes, such as an increased use of GPS devices and accelerometers and a majority of studies now using the R software environment for statistical computing. However, animal movement research still largely focuses on the effect of environmental factors on movement, with motion and navigation continuing to receive little attention. A search of topics based on words featured in abstracts revealed a clustering of papers among marine and terrestrial realms, as well as applications and methods across taxa. We discuss the potential for technological and methodological advances in the field to lead to more integrated and interdisciplinary research and an increased exploration of key movement processes such as navigation, as well as the evolutionary, physiological, and life-history consequences of movement

The type III effector EspF coordinates membrane trafficking by the spatiotemporal activation of two eukaryotic signaling pathways

Bacterial toxins and effector proteins hijack eukaryotic enzymes that are spatially localized and display rapid signaling kinetics. However, the molecular mechanisms by which virulence factors engage highly dynamic substrates in the host cell environment are poorly understood. Here, we demonstrate that the enteropathogenic Escherichia coli (EPEC) type III effector protein EspF nucleates a multiprotein signaling complex composed of eukaryotic sorting nexin 9 (SNX9) and neuronal Wiskott-Aldrich syndrome protein (N-WASP). We demonstrate that a specific and high affinity association between EspF and SNX9 induces membrane remodeling in host cells. These membrane-remodeling events are directly coupled to N-WASP/Arp2/3–mediated actin nucleation. In addition to providing a biochemical mechanism of EspF function, we find that EspF dynamically localizes to membrane-trafficking organelles in a spatiotemporal pattern that correlates with SNX9 and N-WASP activity in living cells. Thus, our findings suggest that the EspF-dependent assembly of SNX9 and N-WASP represents a novel form of signaling mimicry used to promote EPEC pathogenesis and gastrointestinal disease

The Massive and Distant Clusters of WISE Survey VI: Stellar Mass Fractions of a Sample of High-Redshift Infrared-selected Clusters

We present measurements of the stellar mass fractions ($f_\star$) for a sample of high-redshift ($0.93 \le z \le 1.32$) infrared-selected galaxy clusters from the Massive and Distant Clusters of WISE Survey (MaDCoWS) and compare them to the stellar mass fractions of Sunyaev-Zel'dovich (SZ) effect-selected clusters in a similar mass and redshift range from the South Pole Telescope (SPT)-SZ Survey. We do not find a significant difference in mean $f_\star$ between the two selection methods, though we do find an unexpectedly large range in $f_\star$ for the SZ-selected clusters. In addition, we measure the luminosity function of the MaDCoWS clusters and find $m^*= 19.41\pm0.07$, similar to other studies of clusters at or near our redshift range. Finally, we present SZ detections and masses for seven MaDCoWS clusters and new spectroscopic redshifts for five MaDCoWS clusters. One of these new clusters, MOO J1521+0452 at $z=1.31$, is the most distant MaDCoWS cluster confirmed to date.Comment: Accepted to Ap

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics

Background: Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives. Methods: Our tool, “OMIM Explorer” (http://www.omimexplorer.com), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries—in essence, generating a computationally assisted differential diagnosis informed by the individual’s personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes. Results: We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants. Conclusions: Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge