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1.  Bird Radar Validation in the Field by Time-Referencing Line-Transect Surveys 
PLoS ONE  2013;8(9):e74129.
Track-while-scan bird radars are widely used in ornithological studies, but often the precise detection capabilities of these systems are unknown. Quantification of radar performance is essential to avoid observational biases, which requires practical methods for validating a radar’s detection capability in specific field settings. In this study a method to quantify the detection capability of a bird radar is presented, as well a demonstration of this method in a case study. By time-referencing line-transect surveys, visually identified birds were automatically linked to individual tracks using their transect crossing time. Detection probabilities were determined as the fraction of the total set of visual observations that could be linked to radar tracks. To avoid ambiguities in assigning radar tracks to visual observations, the observer’s accuracy in determining a bird’s transect crossing time was taken into account. The accuracy was determined by examining the effect of a time lag applied to the visual observations on the number of matches found with radar tracks. Effects of flight altitude, distance, surface substrate and species size on the detection probability by the radar were quantified in a marine intertidal study area. Detection probability varied strongly with all these factors, as well as species-specific flight behaviour. The effective detection range for single birds flying at low altitude for an X-band marine radar based system was estimated at ∼1.5 km. Within this range the fraction of individual flying birds that were detected by the radar was 0.50±0.06 with a detection bias towards higher flight altitudes, larger birds and high tide situations. Besides radar validation, which we consider essential when quantification of bird numbers is important, our method of linking radar tracks to ground-truthed field observations can facilitate species-specific studies using surveillance radars. The methodology may prove equally useful for optimising tracking algorithms.
doi:10.1371/journal.pone.0074129
PMCID: PMC3774623  PMID: 24066103
2.  Fit-for-Purpose: Species Distribution Model Performance Depends on Evaluation Criteria – Dutch Hoverflies as a Case Study 
PLoS ONE  2013;8(5):e63708.
Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species’ data characteristics (i.e. sample size, spatial distribution).
doi:10.1371/journal.pone.0063708
PMCID: PMC3653807  PMID: 23691089
3.  Analysis and visualization of animal movement 
Biology Letters  2011;8(1):6-9.
The interdisciplinary workshop ‘Analysis and Visualization of Moving Objects’ was held at the Lorentz Centre in Leiden, The Netherlands, from 27 June to 1 July 2011. It brought together international specialists from ecology, computer science and geographical information science actively involved in the exploration, visualization and analysis of moving objects, such as marine reptiles, mammals, birds, storms, ships, cars and pedestrians. The aim was to share expertise, methodologies, data and common questions between different fields, and to work towards making significant advances in movement research. A data challenge based on GPS tracking of lesser black-backed gulls (Larus fuscus) was used to stimulate initial discussions, cross-fertilization between research groups and to serve as an initial focus for activities during the workshop.
doi:10.1098/rsbl.2011.0764
PMCID: PMC3259983  PMID: 21865243
GPS; movement ecology; segmentation; tracking; trajectories; visual analytics
4.  From Sensor Data to Animal Behaviour: An Oystercatcher Example 
PLoS ONE  2012;7(5):e37997.
Animal-borne sensors enable researchers to remotely track animals, their physiological state and body movements. Accelerometers, for example, have been used in several studies to measure body movement, posture, and energy expenditure, although predominantly in marine animals. In many studies, behaviour is often inferred from expert interpretation of sensor data and not validated with direct observations of the animal. The aim of this study was to derive models that could be used to classify oystercatcher (Haematopus ostralegus) behaviour based on sensor data. We measured the location, speed, and tri-axial acceleration of three oystercatchers using a flexible GPS tracking system and conducted simultaneous visual observations of the behaviour of these birds in their natural environment. We then used these data to develop three supervised classification trees of behaviour and finally applied one of the models to calculate time-activity budgets. The model based on accelerometer data developed to classify three behaviours (fly, terrestrial locomotion, and no movement) was much more accurate (cross-validation error = 0.14) than the model based on GPS-speed alone (cross-validation error = 0.35). The most parsimonious acceleration model designed to classify eight behaviours could distinguish five: fly, forage, body care, stand, and sit (cross-validation error = 0.28); other behaviours that were observed, such as aggression or handling of prey, could not be distinguished. Model limitations and potential improvements are discussed. The workflow design presented in this study can facilitate model development, be adapted to a wide range of species, and together with the appropriate measurements, can foster the study of behaviour and habitat use of free living animals throughout their annual routine.
doi:10.1371/journal.pone.0037997
PMCID: PMC3365100  PMID: 22693586
5.  Birds flee en mass from New Year’s Eve fireworks 
Behavioral Ecology  2011;22(6):1173-1177.
Anthropogenic disturbances of wildlife, such as noise, human presence, hunting activity, and motor vehicles, are becoming an increasing concern in conservation biology. Fireworks are an important part of celebrations worldwide, and although humans often find fireworks spectacular, fireworks are probably perceived quite differently by wild animals. Behavioral responses to fireworks are difficult to study at night, and little is known about the negative effects fireworks may have on wildlife. Every year, thousands of tons of fireworks are lit by civilians on New Year’s Eve in the Netherlands. Using an operational weather radar, we quantified the reaction of birds to fireworks in 3 consecutive years. Thousands of birds took flight shortly after midnight, with high aerial movements lasting at least 45 min and peak densities measured at 500 m altitude. The highest densities were observed over grasslands and wetlands, including nature conservation sites, where thousands of waterfowl rest and feed. The Netherlands is the most important winter staging area for several species of waterfowl in Europe. We estimate that hundreds of thousands of birds in the Netherlands take flight due to fireworks. The spatial and temporal extent of disturbance is substantial, and potential consequences are discussed. Weather radar provides a unique opportunity to study the reaction of birds to fireworks, which has otherwise remained elusive.
doi:10.1093/beheco/arr102
PMCID: PMC3199162  PMID: 22476363
birds; disturbance; fireworks; flight; Natura 2000; radar; waterfowl
6.  Integrating Meteorology into Research on Migration 
Atmospheric dynamics strongly influence the migration of flying organisms. They affect, among others, the onset, duration and cost of migration, migratory routes, stop-over decisions, and flight speeds en-route. Animals move through a heterogeneous environment and have to react to atmospheric dynamics at different spatial and temporal scales. Integrating meteorology into research on migration is not only challenging but it is also important, especially when trying to understand the variability of the various aspects of migratory behavior observed in nature. In this article, we give an overview of some different modeling approaches and we show how these have been incorporated into migration research. We provide a more detailed description of the development and application of two dynamic, individual-based models, one for waders and one for soaring migrants, as examples of how and why to integrate meteorology into research on migration. We use these models to help understand underlying mechanisms of individual response to atmospheric conditions en-route and to explain emergent patterns. This type of models can be used to study the impact of variability in atmospheric dynamics on migration along a migratory trajectory, between seasons and between years. We conclude by providing some basic guidelines to help researchers towards finding the right modeling approach and the meteorological data needed to integrate meteorology into their own research.
doi:10.1093/icb/icq011
PMCID: PMC2931313  PMID: 20811515

Results 1-6 (6)