Collision risk of Montagu’s Harriers Circus pygargus with wind turbines derived from high-resolution GPS tracking

Flight behaviour characteristics such as flight altitude and avoidance behaviour determine the species-specific collision risk of birds with wind turbines. However, traditional observational methods exhibit limited positional accuracy. High-resolution GPS telemetry represents a promising method to overcome this drawback. In this study, we used three-dimensional GPS tracking data including high-accuracy tracks recorded at 3-s intervals to investigate the collision risk of breeding male Montagu's Harriers Circus pygargus in the Dutch–German border region. Avoidance of wind turbines was quantified by a novel approach comparing observed flights to a null model of random flight behaviour. On average, Montagu's Harriers spent as much as 8.2 h per day in flight. Most flights were at low altitude, with only 7.1% within the average rotor height range (RHR; 45–125 m). Montagu's Harriers showed significant avoidance behaviour, approaching turbines less often than expected, particularly when flying within the RHR (avoidance rate of 93.5%). For the present state, with wind farms situated on the fringes of the regional nesting range, collision risk models based on our new insights on flight behaviour indicated 0.6–2.0 yearly collisions of adult males (as compared with a population size of c. 40 pairs). However, the erection of a new wind farm inside the core breeding area could markedly increase mortality (up to 9.7 yearly collisions). If repowering of the wind farms was carried out using low-reaching modern turbines (RHR 36–150 m), mortality would more than double, whereas it would stay approximately constant if higher turbines (RHR 86–200 m) were used. Our study demonstrates the great potential of high-resolution GPS tracking for collision risk assessments. The resulting information on collision-related flight behaviour allows for performing detailed scenario analyses on wind farm siting and turbine design, in contrast to current environmental assessment practices. With regard to Montagu's Harriers, we conclude that although the deployment of higher wind turbines represents an opportunity to reduce collision risk for this species, precluding wind energy developments in core breeding areas remains the most important mitigation measure.     

Estimating flight height and flight speed of breeding Piping Plovers

Collisions with wind turbines are an increasing conservation concern for migratory birds that already face many threats. Existing collision‐risk models take into account parameters of wind turbines and bird flight behavior to estimate collision probability and mortality rates. Two behavioral characteristics these models require are the proportion of birds flying at the height of the rotor swept‐zone and the flight speed of birds passing through the rotor swept‐zone. In recent studies, investigators have measured flight height and flight speed of migrating birds using fixed‐beam radar and thermal imaging. These techniques work well for fixed areas where migrants commonly pass over, but they cannot readily provide species‐specific information. We measured flight heights of a nesting shorebird, the federally threatened Piping Plover (Charadrius melodus), using optical range finding and measured flight speed using videography. Several single‐turbine wind projects have been proposed for the Atlantic coast of the United States where they may pose a potential threat to these plovers. We studied Piping Plovers in New Jersey and Massachusetts during the breeding seasons of 2012 and 2013. Measured flight heights ranged from 0.7 to 10.5 m with a mean of 2.6 m (N = 19). Concurrent visually estimated flight heights were all within 2 m of measured heights and most within 1 m. In separate surveys, average visually estimated flight height was 2.6 m (N = 1674) and ranged from 0.25 m to 40 m. Average calculated flight speed was 9.30 m/s (N = 17). Optical range finding was challenging, but provided a useful way to calibrate visual estimates where frames of reference were lacking in the environment. Our techniques provide comparatively inexpensive, replicable procedures for estimating turbine collision‐risk parameters where the focus is on discrete nesting areas of specific species where birds follow predictable flight paths.     

Predicting Bald Eagle Collision at Wind Energy Facilities

Bald eagles (Haliaeetus leucocephalus) are currently protected in the United States under the Bald and Golden Eagle Protection Act of 1940 and Migratory Bird Treaty Act of 1918. Given these protections and the increasing development of wind energy throughout the United States, it is important for regulators and the wind industry to understand the risk of bald eagle collisions with wind turbines. Prior probability distributions for eagle exposure rates and collision rates have been developed for golden eagles (Aquila chrysaetos) by the United States Fish and Wildlife Service (USFWS). Given similar information has not been available for bald eagles, the current recommendation by the USFWS is to use the prior probability distributions developed using data collected on golden eagles to predict take for bald eagles. But some evidence suggests that bald and golden eagles may be at different risk for collision with wind turbines and the prior probability distributions developed for golden eagles may not be appropriate for bald eagles. We developed prior probability distributions using data collected at MidAmerican Energy Company's operating wind energy facilities in Iowa, USA, from December 2014 to March 2017 for bald eagle exposure rates and collision rates. The prior probability distribution for collision rate developed for bald eagles has a lower mean collision rate and less variability relative to that developed for golden eagles. We determined that the prior probability distributions specific to bald eagles from these operating facilities are a better starting point for predicting take for bald eagles at operating wind energy facilities in an agricultural landscape than those developed for golden eagles. © 2021 The Wildlife Society.     

Flying Beetles Respond as Moths Predict: Optomotor Anemotaxis to Pheromone Plumes at Different Heights

The current level of understanding of orientation mechanisms used by flying insects responding to pheromone sources, based almost entirely on studies of moths and flies, allows clear predictions to be made of how other, hitherto little-studied insect taxa, such as beetles (Coleoptera), should behave if the same mechanisms are used. Results are presented of the first test of such set of predictions, the effect of flight height on ground speed, on a beetle, Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae). The beetle P. truncatus flew upwind toward the source of horizontal pheromone plumes and responded to the movement of visible patterns on the floor of a sustained flight tunnel. Beetles flying at a greater height from the floor were less responsive to moving floor patterns. The flight speeds of P. truncatus increased with flight altitude, as found with moths, suggesting that they use orientation mechanism similar to those of moths.     

Virtual plankton: A novel approach to the investigation of aquatic predator‐prey interactions

Small‐scale zooplankton swimming behaviors can affect aquatic predator‐prey interactions. Difficulties in controlling prey swimming behavior however, have restricted the ability to test hypotheses relating differences in small‐scale swimming behavior to frequency of predation by fish. We report here a Virtual Plankton (VP) system that circumvents this problem by allowing the observation of fish “preying"on computer‐generated prey images whose size, shape, color and swimming behavior can be precisely controlled. Two experiments were performed in which bluegill sunfish (Lepomis macrochirus) were given a choice of either two VP images, one of which moved twice as fast as the other, or six VP, one of which moved either faster (1.25 x, 1.5 x or 2 x ) or slower (0.5 x) than the other five. Current predator‐prey models based on encounter probabilities and prey visibility predict that moving faster increases predation risk and conversely, moving slower decreases predation risk. In agreement with existing predator‐prey models, in both experiments, fish chose faster moving VP significantly more often than their slower moving neighbors. Contrary to the predictions of existing models, in the second experiment with six VP, the rate at which fish chose a prey image moving half as fast as the five surrounding images did not differ significantly from the rate predicted by chance(l/6). These results suggest that current fish‐zooplankton predation models would benefit by the incorporation of small‐scale swimming behavior and assessments of its influence on overall prey visibility.     

Flight activity of the damson–hop aphid, Phorodon humuli.

Flight activity of Phorodon humuli was monitored using suction traps, laboratory studies and mark and recapture experiments. Emigrants were trapped as they flew from a Myrobalan (Prunus cerasifera) hedge and among dwarf hops (Humulus lupulus). Daily flight curves were bimodal with 69% and 38% of emigrants caught in the morning peak near Myrobalan and among hops, respectively. The median period of flight activity was from 2 h after sunrise until 30 min before sunset. The lower temperature for flight was 13.5°C in the field and 14.9°C for take off in the laboratory. Variations in wind speed had little effect on flight activity explaining <2.5% of the total variance among insect counts. The percentage of emigrants on hop declined exponentially with time. The relationship, y= 10.9(±2.0) + 64.3(±2.3) × 0.92(±0.01)^t where t = daylight hours (standard error in parentheses), explained 98.3% of the variance. Hence, 62% of new arrivals flew within 1 day of arrival and 79% within 2 days. Similar numbers arrived as departed at 08:30, 10:30 and 12:30 h, but at 14:30 h twice as many arrived than departed and at 16:30 h, the accumulation was threefold. Daily flight curves of return migrants and males leaving hop were bimodal with 70% and 80%, respectively, trapped in the earlier peak. In the field, the median lower temperature for flight was 13.2°C for return migrants and a nonsignificantly different 12.8°C for males. The mean temperature for take off by return migrants was 15.7°C in the laboratory.     

Evaluation of low-intensity physical activity by triaxial accelerometry

Objective: To develop regression‐based equations that estimate physical activity ratios [energy expenditure (EE) per minute/sleeping metabolic rate] for low‐to‐moderate intensity activities using total acceleration obtained by triaxial accelerometry. Research Methods and Procedures: Twenty‐one Japanese adults were fitted with a triaxial accelerometer while also in a whole‐body human calorimeter for 22.5 hours. The protocol time was composed of sleep (8 hours), four structured activity periods totaling 4 hours (sitting, standing, housework, and walking on a treadmill at speeds of 71 and 95 m/min, 2 × 30 minutes for each activity), and residual time (10.5 hours). Acceleration data (milligausse) from the different periods and their relationship to physical activity ratio obtained from the human calorimeter allowed for the development of EE equations for each activity. The EE equations were validated on the residual times, and the percentage difference for the prediction errors was calculated as (predicted value ? measured value)/measured value × 100. Results: Using data from triaxial accelerations and the ratio of horizontal to vertical accelerations, there was relatively high accuracy in identifying the four different periods of activity. The predicted EE (882 ± 150 kcal/10.5 hours) was strongly correlated with the actual EE measured by human calorimetry (846 ± 146 kcal/10.5 hours, r = 0.94 p < 0.01), although the predicted EE was slightly higher than the measured EE. Discussion: Triaxial accelerometry, when total, vertical, and horizontal accelerations are utilized, can effectively evaluate different types of activities and estimate EE for low‐intensity physical activities associated with modern lifestyles.     

Spatially Explicit Assessment of Sandhill Crane Exposure to Potential Transmission Line Collision Risk

Infrastructure development can affect avian populations through direct collision mortality. Estimating the exposure of local bird populations to the risk of direct mortality from infrastructure development requires site- and species-specific data, which managers may find difficult to obtain at the scale over which management decisions are made. We quantify the potential exposure of sandhill cranes (Antigone canadensis) to collision with horizontal structures (e.g., transmission lines) within vital wintering grounds of the Middle Rio Grande Valley (MRGV), New Mexico, USA, 2014–2020. Limited maneuverability and visual acuity make sandhill cranes vulnerable to collisions with infrastructure bisecting their flight paths. We used data from 81 global positioning system (GPS)-tagged cranes to estimate the spatially explicit flight height distribution along the MRGV, the passage rate across hypothetical transmission lines, and the resulting exposure rate (exposed passes/crane/day). The exposure rate ranged from 0–0.28 exposed passes/crane/day (median = 0.015) assuming an exposure zone of 7–60 m above ground level, and identified hotspots of potential exposure within the MRGV. Mapped exposure rates can assist in the siting of proposed high-voltage transmission lines, or other infrastructure, to limit effects on sandhill cranes and other avian species at risk of collision. Our approach can be replicated and applied in similar situations where birds are exposed to possible collision with power lines. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.     

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.     

Adaptation at Specific Loci. III. Field Behavior and Survivorship Differences among Colias Pgi Genotypes Are Predictable from IN VITRO Biochemistry

Previous work on the phosphoglucose isomerase (PGI) polymorphism of Colias butterflies led to predictions concerning aspects of differential survivorship and fecundity among the polymorphic genotypes in the wild. Explicit assumptions underlying these predictions were that functional differences among genotypes at the in vitro biochemical level reflected roughly corresponding differences in vivo, and that the interaction of such differences with the thermal dependence of flight capacity was correctly understood. All those predictions tested were confirmed. We now report experimental designs for testing three more of these predictions. They concern both differential survivorship and the flight activity component of differential fecundity. We find, as predicted: (1) certain heterozygotes, kinetically most effective at low temperature, begin flight earlier in the day than do other genotypes (six replicates); (2) among the three most common genotypes, the order of kinetic effectiveness, i.e., 3/4 > 3/3 >> 4/4, is reflected in asymmetric order of heterotic advantage, 3/4 > 3/3 >> 4/4, in time of flight initiation, breadth of flight time and/or overall flight density through the day (six replicates); (3) under high temperature stress, the usual survivorship advantage of kinetically favored genotypes is reversed, and the three most thermally stable genotypes show better survivorship.——These results strengthen further the case for direct natural selection on this locus. Implications for population sampling practices, for studies of the adaptive organization of metabolism, and for studies of the interaction of genetic variation with patterns of environmental variability are discussed.     

Components of error in predictions of species compositional change

Abstract. A method is given for measuring two components of error (rate and direction) in predictions of compositional change through time. Observed compositional change between two times can be represented as a vector between two points in multidimensional species space. The point at the tail of this vector is the species composition at one particular time. A vector of predicted compositional change will diverge from the vector of observed change to some degree. The error in the predicted rate of change is measured by the difference between the lengths of the two vectors. The error in the predicted direction of change is measured by the angle between the vectors. The cosine of this angle is a non-standardized correlation coefficient (r_n) between the predicted and observed species compositions. The quantity 1 - r_n² measures the error in direction of the predicted dynamics without being influenced by the overall rate of change. These measures in Euclidean space have useful counterparts in city-block space. The method is illustrated by comparing actual long-term changes in Midwestern old-growth forests with the changes predicted by a growth and yield model, TWIGS.     

An ensemble model for predicting Rhopalosiphum padi abundance

A novel modeling method is proposed to predict the abundance of the main vector of barley yellow dwarf virus in autumn sown cereal crops. An ensemble model based on artificial neural networks (ANN) was developed to predict the number of Rhopalosiphum padi (L.) (Homoptera: Aphididae) caught in traps during the autumn flight period at Lincoln, Canterbury, New Zealand, over the period 1982–2003. Artificial neural networks were trained using historical weather data and aphid data collected from a suction trap. Model results were compared with those obtained using multiple regression (MR) models using the same independent variables. Both ANN and MR models were validated by leave‐one‐out validation, in other words, by sequentially jackknifing each year out of the data set, fitting a model to the remaining data, then using that model to predict the number of aphids for each jackknifed year. A linear ensemble of ANN models further improved the predictions and represented the trends in the number of aphids over the 22‐year period very well. The r² between the predicted and observed numbers of aphids for the ANN models changed from 0.68 to 0.83 using the linear ensemble model, but the ensemble approach did not change the prediction for the MR models. The absolute mean error (ABSME) of prediction was much lower for the ANN ensemble predictions compared to that for the MR models. The ABMSE for the ANN models dropped from 109 to 86 aphids compared to an ABMSE reduction from 245 to 220 aphids for the MR models. We discuss the potential for ensemble models for predicting insect abundance when long‐term historical data are available.     

Universal Optimization of Flight Initiation Distance and Habitat-Driven Variation in Escape Tactics in a Namibian Lizard Assemblage

Some aspects of escape predicted by theoretical models are intended to apply universally. For example, flight initiation distance (distance between an approaching predator and prey when escape begins) is predicted from predation risk and the costs of escaping. Escape tactics and refuge selection are not currently predicted by theoretical models, but are expected to vary with structural features of the habitat. One way of studying such variation is to compare aspects of antipredatory behavior among sympatric species that differ in habitat or microhabitat use. In an assemblage of lizards in northwestern Namibia, we conducted experiments to test predictions of escape theory for three risk factors in representatives of three families and observed escape tactics in additional species. As predicted by escape theory, flight initiation distance increased with directness of a predator's approach and predator speed in Agama planiceps, Mabuya acutilabris, and Rhotropus boultoni, and with distance from refuge in M. acutilabris. As predicted by theory, the probability of entering refuge increased with risk in R. boultoni. All available data indicate that flight initiation distance and refuge entry by lizards conform to theoretical predictions. Escape tactics varied greatly as a function of habitat type: (1) arboreal species fled up and around trees and sometimes entered tree holes; (2) saxicolous species used rock crevices as refuges, but differed in tactics prior to entering refuges; and (3) terrestrial species fled into bushes or other vegetation, often to the far sides of them. Some M. acutilabris entered small animal burrows or buried themselves in sand beneath bushes. Escape tactics varied even among congeners in Mabuya, highlighting the important effect of habitat structure on them. Although habitat partitioning has traditionally been viewed as favoring species coexistence, an interesting by‐product appears to be structuring of escape tactics in lizard communities.     

单木生物量模型估计区域尺度生物量的不确定性

采用系统抽样体系江西省固定样地杉木连续观测数据和生物量数据,通过Monte Carlo法反复模拟由单木生物量模型推算区域尺度地上生物量的过程,估计了江西省杉木地上总生物量。基于不同水平建模样本量n及不同决定系数R~2的设计,分别研究了单木生物量模型参数变异性及模型残差变异性对区域尺度生物量估计不确定性的影响。研究结果表明:2009年江西省杉木地上生物量估计值为(19.84±1.27)t/hm~2,不确定性占生物量估计值约6.41%。生物量估计值和不确定性值达到平稳状态所需的运算时间随建模样本量及决定系数R~2的增大而减小;相对于模型参数变异性,残差变异性对不确定性的影响更小。     

Finding confidence limits on population growth rates: Bootstrap and analytic methods

When predicting population dynamics, the value of the prediction is not enough and should be accompanied by a confidence interval that integrates the whole chain of errors, from observations to predictions via the estimates of the parameters of the model. Matrix models are often used to predict the dynamics of age- or size-structured populations. Their parameters are vital rates. This study aims (1) at assessing the impact of the variability of observations on vital rates, and then on model’s predictions, and (2) at comparing three methods for computing confidence intervals for values predicted from the models. The first method is the bootstrap. The second method is analytic and approximates the standard error of predictions by their asymptotic variance as the sample size tends to infinity. The third method combines use of the bootstrap to estimate the standard errors of vital rates with the analytical method to then estimate the errors of predictions from the model. Computations are done for an Usher matrix models that predicts the asymptotic (as time goes to infinity) stock recovery rate for three timber species in French Guiana. Little difference is found between the hybrid and the analytic method. Their estimates of bias and standard error converge towards the bootstrap estimates when the error on vital rates becomes small enough, which corresponds in the present case to a number of observations greater than 5000 trees.     

Timing of vole hunting in aerial predators: RAPTOR GROUP RUG/RIJP*

In a short but intense field investigation, surface activity of common voles in a cropped lucerne field was assayed by live-trapping while, simultaneously, hunting activity and yield of three species of raptors were recorded by continuous observation. Pronounced short-term rhythms in trappability of the vole population ran parallel with fluctuations in yield per hour of flight-hunt of hen harriers and kestrels. These raptors, as well as Rough-legged buzzards, hunted more at times of increased vole surface activity; hen harriers saved c. 15 hours of flight-hunt per day by such temporal adjustment, corresponding to about 12% of their daily energy intake. Voles suffered a predation rate of an estimated 0 2% per day; under such heavy predation and temporal concentration of raptor hunting at times of increased vole activity, surface feeding in synchrony with the vole majority was associated with increased risk of predation.     

Likelihood based population viability analysis in the presence of observation error

Population viability analysis (PVA) entails calculation of extinction risk, as defined by various extinction metrics, for a study population. These calculations strongly depend on the form of the population growth model and inclusion of demographic and/or environmental stochasticity. Form of the model and its parameters are determined based on observed population time series data. A typical population time series, consisting of estimated population sizes, inevitably has some observation error and likely has missing observations. In this paper, we present a likelihood based PVA in the presence of observation error and missing data. We illustrate the importance of incorporation of observation error in PVA by reanalyzing the population time series of song sparrow Melospiza melodia on Mandarte Island, British Columbia, Canada from 1975–1998. Using Akaike information criterion we show that model with observation error fits the data better than the one without observation error. The extinction risks predicted by with and without observation error models are quite different. Further analysis of possible causes for observation error revealed that some component of the observation error might be due to unreported dispersal. A complete analysis of such data, thus, would require explicit spatial models and data on dispersal along with observation error. Our conclusions are, therefore, two‐fold: 1) observation errors in PVA matter and 2) integrating these errors in PVA is not always enough and can still lead to important biases in parameter estimates if other processes such as dispersal are ignored.     

Where eagles soar: Fine‐resolution tracking reveals the spatiotemporal use of differential soaring modes in a large raptor

Unlike smaller raptors, which can readily use flapping flight, large raptors are mainly restricted to soaring flight due to energetic constraints. Soaring comprises of two main strategies: thermal and orographic soaring. These soaring strategies are driven by discrete uplift sources determined by the underlying topography and meteorological conditions in an area. High‐resolution GPS tracking of raptor flight allows the identification of these flight strategies and interpretation of the spatiotemporal occurrence of thermal and orographic soaring. In this study, we develop methods to identify soaring flight behaviors from high‐resolution GPS tracking data of Verreaux’s eagle Aquila verreauxii and analyze these data to understand the conditions that promote the use of thermal and orographic soaring. We use these findings to predict the use of soaring flight both spatially (across the landscape) and temporally (throughout the year) in two topographically contrasting regions in South Africa. We found that topography is important in determining the occurrence of soaring flight and that thermal soaring occurs in relatively flat areas which are likely to have good thermal uplift availability. The predicted use of orographic soaring was predominately determined by terrain slope. Contrary to our expectations, the topography and meteorology of eagle territories in the Sandveld promoted the use of soaring flight to a greater extent than in territories in the more mountainous Cederberg region. Spatiotemporal mapping of predicted flight behaviors can broaden our understanding of how large raptors like the Verreaux’s eagle use their habitat and how that links to energetics (as the preferential use of areas that maximize net energy gain is expected), reproductive success, and ultimately population dynamics. Understanding the fine‐scale landscape use and environmental drivers of raptor flight can also help to predict and mitigate potential detrimental effects of anthropogenic developments, such as mortality via collision with wind turbines.     

Influence of temperature and water vapour pressure on the flight activity ofSimulium arcticum Malloch (Diptera: Simuliidae)

The effects of temperature and vapour pressure deficit on the flight activity ofSimulium arcticum were defined under controlled laboratory conditions. Optimum conditions of temperature and vapour pressure deficit for flight activity varied with time of exposure to the environmental conditions. By applying polynomial equations for the various response surfaces it was possible to predict the time-dependent, optimal hygrothermal environment for black-fly flight activity. Greatest variability in flight activity occurred just prior to death of the insects. Mortality of flies after 1 h exposures to the experimental conditions occurred only at high temperatures and vapour pressure deficits. With increased time of exposure, mortality increased at lower temperatures and vapour pressure deficits.     

The diurnal flight activity and influential factors of Frankliniella occidentalis in the greenhouse

Abstract The daily flight activity of western flower thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae) was examined using color, yellow-light and chemical attractant traps in a cucumber greenhouse and under controlled laboratory conditions. In the greenhouse, flying thrips were most abundant between hours 08:00–10:00, declined at mid-day, and then slightly increased during hours 14:00–16:00; however they decreased to a very low level at 18:00. The use of light traps showed no thrip flight activity during the night. The total number of thrips that flew onto cards on rainy or cloudy days was higher than that on sunny days. We reconfirmed that traps treated with attractant attracted 4.0–9.4 times more thrip than the untreated traps. Under laboratory controlled conditions, thrip flight activity was highest under light intensity between 4 000 and 6 000 lux, air temperature of 28°C, and RH of 70%. In addition, starved thrips flew more readily than non-starved thrips.