Quantification of bird migration by radar – a detection probability problem

Besides the scientific interest in the quantification of bird migration, there is an increasing need to quantify bird movements for the assessment of bird collision risk with artificial structures. In many environmental impact studies, the radar method is used in an inappropriate manner. The processing of echoes consists often of counting blips within defined screen fields, and the surveyed volume is estimated without reference to the detection probabilities of different 'target sizes' (radar cross-sections). The aim of this paper is to present a procedure to quantify bird migration reliably using radar by stating the theoretical requirements of every single step of this procedure and presenting methodological solutions using our own radar data from extensive field studies. Our methodological solutions can be applied to various radar systems, including widely used ship radar. The procedure presented involves discriminating the echoes of birds and insects and estimating the different detection probabilities of differently 'sized' birds (radar cross-sections). By ignoring the different detection probabilities, density estimations may be wrong by as much as 400%. We fear that quantification of bird migration and predicted bird numbers affected by collisions with artificial structures are in many cases based on unreliable estimates.     

Extracting bird migration information from C‐band Doppler weather radars

Although radar has been used in studies of bird migration for 60 years, there is still no network in Europe for comprehensive monitoring of bird migration. Europe has a dense network of military air surveillance radars but most systems are not directly suitable for reliable bird monitoring. Since the early 1990s, Doppler radars and wind profilers have been introduced in meteorology to measure wind. These wind measurements are known to be contaminated with insect and bird echoes. The aim of the present research is to assess how bird migration information can be deduced from meteorological Doppler radar output. We compare the observations on migrating birds using a dedicated X‐band bird radar with those using a C‐band Doppler weather radar. The observations were collected in the Netherlands, from 1 March to 22 May 2003. In this period, the bird radar showed that densities of more than one bird per km³ are present in 20% of all measurements. Among these measurements, the weather radar correctly recognized 86% of the cases when birds were present; in 38% of the cases with no birds detected by the bird radar, the weather radar claimed bird presence (false positive). The comparison showed that in this study reliable altitudinal density profiles of birds cannot be obtained from the weather radar. However, when integrated over altitude, weather radar reflectivity is correlated with bird radar density. Moreover, bird flight speeds from both radars show good agreement in 78% of cases, and flight direction in 73% of cases. The usefulness of the existing network of weather radars for deducing information on bird migration offers a great opportunity for a European‐wide monitoring network of bird migration.     

Bird movements at rotor heights measured continuously with vertical radar at a Dutch offshore wind farm

Assessing the impacts of avian collisions with wind turbines requires reliable estimates of avian flight intensities and altitudes, to enable accurate estimation of collision rates, avoidance rates and related effects on populations. At sea, obtaining such estimates visually is limited not only by weather conditions but, more importantly, because a high proportion of birds fly at night and at heights above the range of visual observation. We used vertical radar with automated bird‐tracking software to overcome these limitations and obtain data on the magnitude, timing and altitude of local bird movements and seasonal migration measured continuously at a Dutch offshore wind farm. An estimated 1.6 million radar echoes representing individual birds or flocks were recorded crossing the wind farm annually at altitudes between 25 and 115 m (the rotor‐swept zone). The majority of these fluxes consisted of gull species during the day and migrating passerines at night. We demonstrate daily, monthly and seasonal patterns in fluxes at rotor heights and the influence of wind direction on flight intensity. These data are among the first to show the magnitude and variation of low‐altitude flight activity across the North Sea, and are valuable for assessing the consequences of developments such as offshore wind farms for birds.     

Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation

Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.     

Software control of sensing and stimulation for cardiac electrophysiological study

A software-controlled cardiac stimulator for clinical investigations is described. The stimulator is programmed by the user at a keyboard, while current status and values of parameters are presented on a visual display screen. A menu of predefined cardiac electrophysiological tests is available for user selection. Validity checks on data keyed in by the user and internal checks on safe pacing limits are incorporated in case of malfunction or user error. The system consists of a separate relatively simple isolated sensing and stimulation unit which communicates, via a standard digital input output interface, with a controlling microcomputer. All timing and control functions are performed in software by the computer. The use of high-level FORTRAN as the main programming language provides the system with a high degree of adaptability.     

Waterfowl on weather radar: applying ground-truth to classify and quantify bird movements

ABSTRACT Local and migratory movements aloft have important implications for the ecology and conservation of birds, but are difficult to quantify. Weather surveillance radar (WSR) offers a unique tool for observing movements of birds, but until now has been used primarily to address broad taxonomic questions. Herein, we demonstrate how natural history information and ground‐truthing can be used to answer quantitative and taxon‐specific questions regarding bird movements on WSR. We found that super‐resolution Level II data from the National Oceanic and Atmospheric Administration's mass storage system was the most effective format and source of WSR data, and that several software packages were needed for thorough analysis of WSR data. Using WSR, we identified potential movements of birds emigrating from a waterfowl stopover area in Illinois in fall (1 September–31 December) 2006 and 2007. We compared spatial and temporal patterns of these movements to the natural history of taxa occupying the source habitat and classified these radar targets as dabbling ducks (tribe Anatini). A portable X‐band radar measured the cruising heights of ducks at 400–600 m. During fall 2008, we conducted ground‐truthing with a thermal infrared camera to enumerate birds passing over our field site during nocturnal migration events. This estimate of bird density, paired with an associated sample of WSR echo strength, provided a mean radar cross section the same as dabbling ducks (112.5 cm²) and supported our natural‐history‐based classification. Thermal infrared‐estimated duck densities explained most of the variation (R²= 0.91) in WSR echo strength across seven migration events of varying intensities, suggesting that radar cross sections of dabbling ducks and WSR reflectivity can be used to estimate duck numbers in other comparable contexts. Our results suggest that careful investigation of the spatial and temporal patterns of movements on radar, along with field‐based ground‐truthing, can be used to study and quantify the movements of specific bird taxa.     

The spring migration pattern of arctic birds in southwest Iceland, as recorded by radar

A surveillance radar in southwest Iceland was recorded by time-lapse filming in order to monitor the migration pattern of birds departing from or passing Iceland on their way to high-arctic breeding grounds in late May and early June 1988–1990. An overwhelming majority of the radar echoes from migrating bird flocks departed from Iceland but a few seemed to pass over from further south. Timing of movements and supplementary field observations indicated that mainly four species were involved, i.e. Knot Calidris canutus , Turnstone Arenaria interpres. Sanderling C. alba and Brent Goose Branta bernicla. Departures in late May from stopover sites in Iceland took place mainly in the afternoons, peaking between 1700 and 1900h in all 3 years. The departure intensity was lowest between 0100 and 1300h. Flight paths were generally straight, and the average track direction was towards the northwest (315°), suggesting that the majority of birds were heading for a transglacial migration across the Greenland icecap on their way to breeding grounds in northwest Greenland and northern Canada. Track directions varied with wind, although to a rather small degree, indicating partial drift or pseudodrift. More echoes were registered in easterly winds (tailwinds) and fewer in northerly winds than expected from random. Airspeeds were significantly slower than groundspeeds (average 17.0 and 18.7 m/s, respectively), showing that the birds more often than not benefited from tail wind assistance.     

Design of an automated temperature mapping system for ultrasound or microwave hyperthermia

An automated temperature mapping system was designed to accomplish the following goals: remote control mapping; a maximum position error of 0.5 mm; mapping simultaneously on several channels; real-time screen display on a dedicated computer; to be inexpensive; and have a simple patient interface and set up. A four channel, microstepper system was fabricated for less than $1000 and controlled by an IBM-AT computer. The system utilizes direct drive of Luxtron fibre-optic probes fed through thin flexible Teflon^® tubing which allows for patient movement. The driving and control software were written in the programming language “C”. Mapping parameters for each independent channel include start and stop positions and map increment. The software permits the user to automatically find the maximum temperature along a track in three passes of 2.0, 1.0 and 0.5 mm steps. The latter two passes take five or seven readings centred about the maximum of the previous pass. A high resolution monitor plots the temperatures in real time, overlaying the previous map in a new colour. A screen dump was written to drive a colour printer with the plot information. The computer evaluates each plot to safeguard against any shift in the maximum location. Visualization of orthogonal pullbacks provides rapid feedback and aids in the repositioning of superficial hyperthermia transducers. The time saved over the previous manual mapping methods easily justifies the additional set up time.     

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application – SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary “Manual Initialize” and “Hand Draw” tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.     

湖南省雀形目鸟类新纪录4种

2011年5月～2012年6月,作者在湖南壶瓶山国家级自然保护区进行鸟类资源调查和种群监测的过程中,拍摄到4种雀形目鸟类,经分类鉴定为灰翅鸫(Turdus boulboul)、蓝喉仙鹟(Cyornis rubeculoides)、灰眉岩鹀(Emberiza godlewskii)和银脸长尾山雀(Aegithalos fuliginosus),均为湖南省鸟类新纪录。     

WSR-88D doppler radar detection of corn earworm moth migration

Corn earworm (Lepidoptera: Noctuidae) (CEW) populations infesting one crop production area may rapidly migrate and infest distant crop production areas. Although entomological radars have detected corn earworm moth migrations, the spatial extent of the radar coverage has been limited to a small horizontal view above crop production areas. The Weather Service Radar (version 88D) (WSR-88D) continuously monitors the radar-transmitted energy reflected by, and radial speed of, biota as well as by precipitation over areas that may encompass crop production areas. We analyzed data from the WSR-88D radar (S-band) at Brownsville, Texas, and related these data to aerial concentrations of CEW estimated by a scanning entomological radar (X-band) and wind velocity measurements from rawinsonde and pilot balloon ascents. The WSR-88D radar reflectivity was positively correlated (r ²?=?0.21) with the aerial concentration of corn earworm-size insects measured by a scanning X-band radar. WSR-88D radar constant altitude plan position indicator estimates of wind velocity were positively correlated with wind speed (r ²?=?0.56) and wind direction (r ²?=?0.63) measured by pilot balloons and rawinsondes. The results reveal that WSR-88D radar measurements of insect concentration and displacement speed and direction can be used to estimate the migratory flux of corn earworms and other nocturnal insects, information that could benefit areawide pest management programs. In turn, identification of the effects of spatiotemporal patterns of migratory flights of corn earworm-size insects on WSR-88D radar measurements may lead to the development of algorithms that increase the accuracy of WSR-88D radar measurements of reflectivity and wind velocity for operational meteorology.     

Track-A-Worm,An Open-Source System for Quantitative Assessment of C. elegans Locomotory and Bending Behavior

A major challenge of neuroscience is to understand the circuit and gene bases of behavior. C. elegans is commonly used as a model system to investigate how various gene products function at specific tissue, cellular, and synaptic foci to produce complicated locomotory and bending behavior. The investigation generally requires quantitative behavioral analyses using an automated single-worm tracker, which constantly records and analyzes the position and body shape of a freely moving worm at a high magnification. Many single-worm trackers have been developed to meet lab-specific needs, but none has been widely implemented for various reasons, such as hardware difficult to assemble, and software lacking sufficient functionality, having closed source code, or using a programming language that is not broadly accessible. The lack of a versatile system convenient for wide implementation makes data comparisons difficult and compels other labs to develop new worm trackers. Here we describe Track-A-Worm, a system rich in functionality, open in source code, and easy to use. The system includes plug-and-play hardware (a stereomicroscope, a digital camera and a motorized stage), custom software written to run with Matlab in Windows 7, and a detailed user manual. Grayscale images are automatically converted to binary images followed by head identification and placement of 13 markers along a deduced spline. The software can extract and quantify a variety of parameters, including distance traveled, average speed, distance/time/speed of forward and backward locomotion, frequency and amplitude of dominant bends, overall bending activities measured as root mean square, and sum of all bends. It also plots worm travel path, bend trace, and bend frequency spectrum. All functionality is performed through graphical user interfaces and data is exported to clearly-annotated and documented Excel files. These features make Track-A-Worm a good candidate for implementation in other labs.     

Digital ‘faces’ of synthetic biology

In silicio design plays a fundamental role in the endeavour to synthesise biological systems. In particular, computer-aided design software enables users to manage the complexity of biological entities that is connected to their construction and reconfiguration. The software’s graphical user interface bridges the gap between the machine-readable data on the algorithmic subface of the computer and its human-amenable surface represented by standardised diagrammatic elements. Notations like the Systems Biology Graphical Notation (SBGN), together with interactive operations such as drag & drop, allow the user to visually design and simulate synthetic systems as ‘bio-algorithmic signs’. Finally, the digital programming process should be extended to the wet lab to manufacture the designed synthetic biological systems. By exploring the different ‘faces’ of synthetic biology, I argue that in particular computer-aided design (CAD) is pushing the idea to automatically produce de novo objects. Multifaceted software processes serve mutually aesthetic, epistemic and performative purposes by simultaneously black-boxing and bridging different data sources, experimental operations and community-wide standards. So far, synthetic biology is mainly a product of digital media technologies that structurally mimic the epistemological challenge to take both qualitative as well as quantitative aspects of biological systems into account in order to understand and produce new and functional entities.     

Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows

Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.     

Measurement of Larval Activity in the Drosophila Activity Monitor

Drosophila larvae are used in many behavioral studies, yet a simple device for measuring basic parameters of larval activity has not been available. This protocol repurposes an instrument often used to measure adult activity, the TriKinetics Drosophila activity monitor (MB5 Multi-Beam Activity Monitor) to study larval activity. The instrument can monitor the movements of animals in 16 individual 8 cm glass assay tubes, using 17 infrared detection beams per tube. Logging software automatically saves data to a computer, recording parameters such as number of moves, times sensors were triggered, and animals’ positions within the tubes. The data can then be analyzed to represent overall locomotion and/or position preference as well as other measurements. All data are easily accessible and compatible with basic graphing and data manipulation software. This protocol will discuss how to use the apparatus, how to operate the software and how to run a larval activity assay from start to finish.     

Mapping migratory bird prevalence using remote sensing data fusion

Background

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA.

Methodology and Principal Findings

A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species.

Conclusion and Significance

Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.     

Size matters in quantitative radar monitoring of animal migration: estimating monitored volume from wingbeat frequency

Quantitative radar studies are an important component of studying the movements of birds. Whether a bird, at a certain distance from the radar, is detected or not depends on its size. The volume monitored by the radar is therefore different for birds of different sizes. Consequently, an accurate quantification of bird movements recorded by small‐scale radar requires an accurate determination of the monitored volume for the objects in question, although this has tended to be ignored. Here, we demonstrate the importance of sensitivity settings for echo detection on the estimated movement intensities of birds of different sizes. The amount of energy reflected from a bird and detected by the radar receiver (echo power) depends not only on the bird's size and on the distance from the radar antenna, but also on the beam shape and the bird's position within this beam. We propose a method to estimate the size of a bird based on the wingbeat frequency, retrieved from the echo‐signal, independent of the absolute echo power. The estimated bird‐size allows calculation of size‐specific monitored volumes, allowing accurate quantification of movement intensities. We further investigate the importance of applying size‐specific monitored volumes to quantify avian movements instead of using echo counts. We also highlight the importance of accounting for size‐specific monitored volume of small scale radar systems, and the necessity of reporting technical information on radar parameters. Applying this framework will increase the quality and validity of quantitative radar monitoring.     

HTSDSF Explorer,A Novel Tool to Analyze High-throughput DSF Screenings

The identification of new drugs for novel therapeutic targets requires the screening of libraries containing tens of thousands of compounds. While experimental screenings are assisted by high-throughput technologies, in target-based biophysical assays, such as differential scanning fluorimetry (DSF), the analysis steps must be calculated manually, often combining several software packages. To simplify the determination of the melting temperature (T_m) of the target and the change induced by ligand binding (ΔT_m), we developed the HTSDSF explorer, a versatile, all-in-one, user-friendly application suite. Implemented as a server-client application, in the primary screenings, HTSDSF explorer pre-analyzes and displays the T_m and ΔT_m results interactively, thereby allowing the user to study hundreds of conditions and select the primary hits in minutes. This application also allows the determination of preliminary binding constants (K_D) through a series of subsequent dose–response assays on the primary hits, thereby facilitating the ranking of validated hits and the advance of drug discovery efforts.