Use of time‐lapse photography and digital image analysis to estimate breeding success of a cliff‐nesting seabird

Development of new methods for obtaining basic demographic data from difficult‐to‐access breeding colonies and easily disturbed species is an important challenge in studies of seabirds. We describe a method that can generate data concerning annual breeding success of cliff‐nesting seabirds or other colonial birds with open nests. Our method requires only a single visit to a colony every second or third year, and is based on the use of automated time‐lapse photography. To test our method, we used time‐lapse photos to examine the breeding success of Thick‐billed Murres (Uria lomvia) in two breeding colonies in Greenland during the years 2011, 2012, and 2014. Based on the analysis of time‐lapse photos, we found that hatching success during the 3 yr of our study ranged from 60% to 81%, fledging success from 89% to 95%, and breeding success from 53% to 74% (Table 1). Use of digital image analysis made it possible to differentiate between breeding and non‐breeding birds and determine if and when breeding attempts failed or succeeded. The key to making our method a realistic long‐term monitoring technique is the use of an automated, formal image analysis to process the thousands of photos from the time‐lapse cameras and, more specifically, to reduce a large number of photos to a manageable number. Using our method, we needed 12–22 h per study plot, depending on the number of breeding sites per plot (range = 47–127) and whether it was the first or the second time the plot was analyzed, to obtain our estimates of hatching, fledging, and breeding success. This included time for data preparation, image analyses, visual inspections, and summarizing data in a spreadsheet. We found that our estimates of breeding success were comparable to those obtained by direct observation in the field. An important aspect of using time‐lapse technology is to foresee potential reasons why time‐lapse cameras might stop taking pictures, for example, equipment failure (camera, timer, or battery) or interference by visitors (e.g., vandalism or theft). As such, thorough testing of time‐lapse systems and selecting camera locations less likely to be disturbed are most important. We believe that use of time‐lapse photography in combination with digital image analysis to estimate breeding success can be useful for determining the breeding success of other cliff‐nesting seabirds and, more generally, other birds that breed in colonies, especially those located in remote areas and where direct observation may disturb birds.     

Computer‐automated bird detection and counts in high‐resolution aerial images: a review

Bird surveys conducted using aerial images can be more accurate than those using airborne observers, but can also be more time‐consuming if images must be analyzed manually. Recent advances in digital cameras and image‐analysis software offer unprecedented potential for computer‐automated bird detection and counts in high‐resolution aerial images. We review the literature on this subject and provide an overview of the main image‐analysis techniques. Birds that contrast sharply with image backgrounds (e.g., bright birds on dark ground) are generally the most amenable to automated detection, in some cases requiring only basic image‐analysis software. However, the sophisticated analysis capabilities of modern object‐based image analysis software provide ways to detect birds in more challenging situations based on a variety of attributes including color, size, shape, texture, and spatial context. Some techniques developed to detect mammals may also be applicable to birds, although the prevalent use of aerial thermal‐infrared images for detecting large mammals is of limited applicability to birds because of the low pixel resolution of thermal cameras and the smaller size of birds. However, the increasingly high resolution of true‐color cameras and availability of small unmanned aircraft systems (drones) that can fly at very low altitude now make it feasible to detect even small shorebirds in aerial images. Continued advances in camera and drone technology, in combination with increasingly sophisticated image analysis software, now make it possible for investigators involved in monitoring bird populations to save time and resources by increasing their use of automated bird detection and counts in aerial images. We recommend close collaboration between wildlife‐monitoring practitioners and experts in the fields of remote sensing and computer science to help generate relevant, accessible, and readily applicable computer‐automated aerial photographic census techniques.     

High‐throughput quantification of chloroplast RNA editing extent using multiplex RT‐PCR mass spectrometry

RNA editing in plants, animals, and humans modifies genomically encoded cytidine or adenosine nucleotides to uridine or inosine, respectively, in mRNAs. We customized the MassARRAY System (Sequenom Inc., San Diego, CA, USA, www.sequenom.com ) to assay multiplex PCR‐amplified single‐stranded cDNAs and easily analyse and display the captured data. By using appropriate oligonucleotide probes, the method can be tailored to any organism and gene where RNA editing occurs. Editing extent of up to 40 different nucleotides in each of either 94 or 382 different samples (3760 or 15 280 editing targets, respectively) can be examined by assaying a single plate and by performing one repetition. We have established this mass spectrometric method as a dependable, cost‐effective and time‐saving technique to examine the RNA editing efficiency at 37 Arabidopsis thaliana chloroplast editing sites at a high level of multiplexing. The high‐throughput editing assay, named Multiplex RT‐PCR Mass Spectrometry (MRMS), is ideal for large‐scale experiments such as identifying population variation, examining tissue‐specific changes in editing extent, or screening a mutant or transgenic collection. Moreover, the required amount of starting material is so low that RNA from fewer than 50 cells can be examined without amplification. We demonstrate the use of the method to identify natural variation in editing extent of chloroplast C targets in a collection of Arabidopsis accessions.     

Phytotyping4D: a light‐field imaging system for non‐invasive and accurate monitoring of spatio‐temporal plant growth

Integrative studies of plant growth require spatially and temporally resolved information from high‐throughput imaging systems. However, analysis and interpretation of conventional two‐dimensional images is complicated by the three‐dimensional nature of shoot architecture and by changes in leaf position over time, termed hyponasty. To solve this problem, Phytotyping^4D uses a light‐field camera that simultaneously provides a focus image and a depth image, which contains distance information about the object surface. Our automated pipeline segments the focus images, integrates depth information to reconstruct the three‐dimensional architecture, and analyses time series to provide information about the relative expansion rate, the timing of leaf appearance, hyponastic movement, and shape for individual leaves and the whole rosette. Phytotyping^4D was calibrated and validated using discs of known sizes, and plants tilted at various orientations. Information from this analysis was integrated into the pipeline to allow error assessment during routine operation. To illustrate the utility of Phytotyping^4D, we compare diurnal changes in Arabidopsis thaliana wild‐type Col‐0 and the starchless pgm mutant. Compared to Col‐0, pgm showed very low relative expansion rate in the second half of the night, a transiently increased relative expansion rate at the onset of light period, and smaller hyponastic movement including delayed movement after dusk, both at the level of the rosette and individual leaves. Our study introduces light‐field camera systems as a tool to accurately measure morphological and growth‐related features in plants.     

Weekend Eating in the United States Is Linked with Greater Energy,Fat, and Alcohol Intake

Objectives: To determine if macronutrient consumption for the U.S. population is greater on weekend days than weekdays. Research Methods and Procedures: The nationally representative 1994 to 1996 Continuing Survey of Food Intakes by Individuals was used for this analysis. Dietary intake was assessed using two independent days of dietary recall data. Ordinary least squares multivariate analysis was used to analyze dietary outcome variables to explore the effect of weekend day vs. weekday intake. Results: This study's results indicate that statistically significant dietary intake differences occur for different days of the week but not for all age groups—nor for all nutrients. The average American, 2 years and older, consumes 82 kcal more per day on each weekend day (Friday through Sunday) than they do on weekdays (Monday through Thursday). These overall increases in dietary intake are significant for the overall sample and are largest for the 19‐ to 50‐year‐old age group; among this age group, the weekend day increase (vs. weekday) is 115 kcal/d. The increased proportions of energy from fat and alcohol consumed on weekends are greater for this adult age group by 0.7% and 1.4%, respectively, whereas the proportion of energy from carbohydrate decreases 1.6%. Discussion: The effects of weekend days on nutrient intake are substantial and should be considered in future clinical and population‐based interventions and in dietary monitoring and research in the U.S.     

Kite aerial photography: a low‐cost method for monitoring seabird colonies

Obtaining aerial high‐resolution images of bird nesting colonies using remote‐sensing technology such as satellite‐based remote sensing, manned aircraft, or Unmanned Aerial Vehicles might not be possible for many researchers due to financial constraints. Kite Aerial Photography (KAP) provides a possible low‐cost alternative. We collected digital images of ground‐nesting seabirds (i.e., cormorants and penguins) in two different ecosystems using a kite‐based platform equipped with consumer‐grade digital cameras with time‐lapse capability to obtain estimates of breeding population size. KAP proved to be an efficient method for acquiring high‐resolution aerial images. We obtained images of colonies of seabirds ranging in size from hundreds to several hundreds of thousands breeding pairs during flights lasting from a few minutes up to three hours, from flat to very steep areas, and in contrasted wind conditions (from 0.5 to 6 Beaufort force). KAP is an efficient low‐cost method for acquiring high‐resolution aerial images and an alternative to ground‐based censuses, especially useful in rugged areas.     

Genotyping‐by‐sequencing for estimating relatedness in nonmodel organisms: Avoiding the trap of precise bias

There has been remarkably little attention to using the high resolution provided by genotyping‐by‐sequencing (i.e., RADseq and similar methods) for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of data that could lead to downward‐biased, yet precise, estimates of relatedness. Here, we assess the applicability of genotyping‐by‐sequencing for relatedness inferences given its relatively high genotyping error rate. Individuals of known relatedness were simulated under genotyping error, allelic dropout and missing data scenarios based on an empirical ddRAD data set, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (Genetics Research, 67, 175) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We also found that the choice of estimator should not rely solely on the strength of correlation between estimated and true relatedness as a strong correlation does not necessarily mean estimates are close to true relatedness. We also demonstrated how even a large SNP data set with genotyping error (allelic dropout or otherwise) or missing data still performs better than a perfectly genotyped microsatellite data set of tens of markers. The simulation‐based approach used here can be easily implemented by others on their own genotyping‐by‐sequencing data sets to confirm the most appropriate and powerful estimator for their data.     

Pseudo‐real‐time retinal layer segmentation for high‐resolution adaptive optics optical coherence tomography

We present a pseudo‐real‐time retinal layer segmentation for high‐resolution Sensorless Adaptive Optics‐Optical Coherence Tomography (SAO‐OCT). Our pseudo‐real‐time segmentation method is based on Dijkstra's algorithm that uses the intensity of pixels and the vertical gradient of the image to find the minimum cost in a geometric graph formulation within a limited search region. It segments six retinal layer boundaries in an iterative process according to their order of prominence. The segmentation time is strongly correlated to the number of retinal layers to be segmented. Our program permits en face images to be extracted during data acquisition to guide the depth specific focus control and depth dependent aberration correction for high‐resolution SAO‐OCT systems. The average processing times for our entire pipeline for segmenting six layers in a retinal B‐scan of 496 × 400 and 240 × 400 pixels are around 25.60 and 13.76 ms, respectively. When reducing the number of layers segmented to only two layers, the time required for a 240 × 400 pixel image is 8.26 ms.     

Comparing Pool‐seq,Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost‐effective sequencing approaches, namely Pool‐seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping‐by‐sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool‐seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool‐seq data showed F_ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F_ST estimates, indicating that individual‐based approaches provided more congruent results than Pool‐seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost‐effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.     

Lightsheet fluorescence lifetime imaging microscopy with wide‐field time‐correlated single photon counting

We report on wide‐field time‐correlated single photon counting (TCSPC)‐based fluorescence lifetime imaging microscopy (FLIM) with lightsheet illumination. A pulsed diode laser is used for excitation, and a crossed delay line anode image intensifier, effectively a single‐photon sensitive camera, is used to record the position and arrival time of the photons with picosecond time resolution, combining low illumination intensity of microwatts with wide‐field data collection. We pair this detector with the lightsheet illumination technique, and apply it to 3D FLIM imaging of dye gradients in human cancer cell spheroids, and C. elegans.     

Using expert knowledge to incorporate uncertainty in cause‐of‐death assignments for modeling of cause‐specific mortality

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause‐specific mortality provide an example of implicit use of expert knowledge when causes‐of‐death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause‐specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause‐of‐death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event‐time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause‐of‐death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause‐of‐death assignment in modeling of cause‐specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause‐specific survival data for white‐tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause‐of‐death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.     

Bring your own camera to the trap: An inexpensive,versatile, and portable triggering system tested on wild hummingbirds

The study of animals in the wild offers opportunities to collect relevant information on their natural behavior and abilities to perform ecologically relevant tasks. However, it also poses challenges such as accounting for observer effects, human sensory limitations, and the time intensiveness of this type of research. To meet these challenges, field biologists have deployed camera traps to remotely record animal behavior in the wild. Despite their ubiquity in research, many commercial camera traps have limitations, and the species and behavior of interest may present unique challenges. For example, no camera traps support high‐speed video recording. We present a new and inexpensive camera trap system that increases versatility by separating the camera from the triggering mechanism. Our system design can pair with virtually any camera and allows for independent positioning of a variety of sensors, all while being low‐cost, lightweight, weatherproof, and energy efficient. By using our specialized trigger and customized sensor configurations, many limitations of commercial camera traps can be overcome. We use this system to study hummingbird feeding behavior using high‐speed video cameras to capture fast movements and multiple sensors placed away from the camera to detect small body sizes. While designed for hummingbirds, our application can be extended to any system where specialized camera or sensor features are required, or commercial camera traps are cost‐prohibitive, allowing camera trap use in more research avenues and by more researchers.     

An easy,flexible solution to attach devices to hedgehogs (Erinaceus europaeus) enables long‐term high‐resolution studies

Bio‐logging is an essential tool for the investigation of behavior, ecology, and physiology of wildlife. This burgeoning field enables the improvement of population monitoring and conservation efforts, particularly for small, elusive animals where data collection is difficult. Device attachment usually requires species‐specific solutions to ensure that data loggers exert minimal influence on the animal’s behavior and physiology, and ensure high reliability of data capture. External features or peculiar body shapes often make securing devices difficult for long‐term monitoring, as in the case with small spiny mammals. Here, we present a method that enables high‐resolution, long‐term investigations of European hedgehogs (Erinaceus europaeus) via GPS and acceleration loggers. We collected data from 17 wild hedgehogs with devices attached between 9 and 42 days. Our results showed that hedgehogs behaved naturally; as individuals curled, moved through dense vegetation, slipped under fences and built regular day nests without any indication of impediment. Our novel method makes it possible to not only attach high‐precision devices for substantially longer than previous efforts, but enables detachment and reattachment of devices to the same individual. This makes it possible to quickly respond to unforeseen events and exchange devices, and overcomes the issue of short battery life common to many lightweight loggers.     

High‐throughput downstream process development for cell‐based products using aqueous two‐phase systems (ATPS) – A case study

The availability of preparative‐scale downstream processing strategies for cell‐based products presents a critical juncture between fundamental research and clinical development. Aqueous two‐phase systems (ATPS) present a gentle, scalable, label‐free, and cost‐effective method for cell purification, and are thus a promising tool for downstream processing of cell‐based therapeutics. Here, the application of a previously developed robotic screening platform that enables high‐throughput cell partitioning analysis in ATPS is reported. In the present case study a purification strategy for two model cell lines based on high‐throughput screening (HTS)‐data and countercurrent distribution (CCD)‐modeling, and validated the CCD‐model experimentally is designed. The obtained data are shown an excellent congruence between CCD‐model and experimental data, indicating that CCD‐models in combination with HTS‐data are a powerful tool in downstream process development. Finally, the authors are shown that while cell cycle phase significantly influences cell partitioning, cell type specific differences in surface properties are the main driving force in charge‐dependent separation of HL‐60 and L929 cells. In order to design a highly robust purification process it is, however, advisable to maintain constant growth conditions.     

Genotyping‐by‐sequencing approaches to characterize crop genomes: choosing the right tool for the right application

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high‐throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping‐by‐sequencing (GBS) methods include over a dozen reduced‐representation sequencing (RRS) approaches and at least four whole‐genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best‐suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small‐ to moderate‐sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost‐effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost‐effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.     

High‐resolution DNA melt‐curve analysis for cost‐effective mass screening of pairwise species interactions

Ecological studies of pairwise interactions are constrained by the methods available for rapid species identification of the interacting organisms. The resolution of data required to characterize species interaction networks at multiple spatio‐temporal scales can be intensive, and therefore laborious and costly to collect. We explore the utility of high‐resolution DNA melt‐curve analysis (HRM) as a rapid species identification method. An approach was developed to identify organisms at the pairwise interaction level, with particular application to cryptic species interactions that are traditionally difficult to study. Here, we selected a challenging application; to identify the presence/absence of pathogenic fungi (Sporothrix inflata, Ophiostoma nigrocarpum and Ophiostoma galeiforme) transported by bark beetle vectors (Hylastes ater and Hylurgus ligniperda). The technique was able to distinguish between different species of DNA within a single, pooled sample. In test applications, HRM was effective in the mass screening and identification of pathogenic fungal species carried by many individual bark beetle vectors (n = 455 beetles screened) across large geographic scales. For two of the fungal species, there was no difference in the frequency of association with either of their vectors, but for the third fungal species there was a shift in vector–pathogen associations across locations. This technique allows rapid, mass screening and characterization of species interactions at a fraction of the time and cost of traditional methods. It is anticipated that this method can be readily applied to explore other cryptic species interactions, or other studies requiring rapid generation of large data sets and/or high‐throughput efficiency.     

Estimating age‐dependent survival from age‐aggregated ringing data—extending the use of historical records

Bird ring‐recovery data have been widely used to estimate demographic parameters such as survival probabilities since the mid‐20th century. However, while the total number of birds ringed each year is usually known, historical information on age at ringing is often not available. A standard ring‐recovery model, for which information on age at ringing is required, cannot be used when historical data are incomplete. We develop a new model to estimate age‐dependent survival probabilities from such historical data when age at ringing is not recorded; we call this the historical data model. This new model provides an extension to the model of Robinson, 2010, Ibis, 152, 651–795 by estimating the proportion of the ringed birds marked as juveniles as an additional parameter. We conduct a simulation study to examine the performance of the historical data model and compare it with other models including the standard and conditional ring‐recovery models. Simulation studies show that the approach of Robinson, 2010, Ibis, 152, 651–795 can cause bias in parameter estimates. In contrast, the historical data model yields similar parameter estimates to the standard model. Parameter redundancy results show that the newly developed historical data model is comparable to the standard ring‐recovery model, in terms of which parameters can be estimated, and has fewer identifiability issues than the conditional model. We illustrate the new proposed model using Blackbird and Sandwich Tern data. The new historical data model allows us to make full use of historical data and estimate the same parameters as the standard model with incomplete data, and in doing so, detect potential changes in demographic parameters further back in time.     

Deeply conserved susceptibility in a multi‐host,multi‐parasite system

Variation in susceptibility is ubiquitous in multi‐host, multi‐parasite assemblages, and can have profound implications for ecology and evolution in these systems. The extent to which susceptibility to parasites is phylogenetically conserved among hosts can be revealed by analysing diverse regional communities. We screened for haemosporidian parasites in 3983 birds representing 40 families and 523 species, spanning ~ 4500 m elevation in the tropical Andes. To quantify the influence of host phylogeny on infection status, we applied Bayesian phylogenetic multilevel models that included a suite of environmental, spatial, temporal, life history and ecological predictors. We found evidence of deeply conserved susceptibility across the avian tree; host phylogeny explained substantial variation in infection status, and results were robust to phylogenetic uncertainty. Our study suggests that susceptibility is governed, in part, by conserved, latent aspects of anti‐parasite defence. This demonstrates the importance of deep phylogeny for understanding present‐day ecological interactions.