Fränzi Korner-Nievergelt

A new method to determine bird and bat fatality at wind energy turbines from carcass searches

Abstract Wind energy is of increasing importance for a sustainable energy supply worldwide. At the same time, concerns about the number of birds and bats being killed at wind turbines have been growing. In this situation, methods for a reliable estimation of bird and bat fatality numbers are needed. To obtain an unbiased estimate of the number of fatalities from fatality searches, the probability to detect the carcass of an animal being killed at a turbine has to be assessed by considering carcass persistence rate, searcher efficiency and the probability that a killed animal falls into a searched area. Here, we describe a new formula to determine the detection probability of birds or bats that are killed at wind turbines and which can estimate the number of fatalities from the number of carcasses found. The formula was developed to analyse a large data set of bats killed at wind turbines in Germany. In simulations, we compared it to three other formulas used in this context. Our new formula seems to have unbiased results when searcher efficiency and carcass removal rate are constant over time. When searcher efficiency or carcass removal rate varied with time, all four formulas showed a similar bias. These comparative results can be used to choose between methods depending on the quality of information available. Our estimator can, for instance, be adapted to different situations including temporal changes of searcher efficiency or carcass removal rate because it is based on an explicit process model.

Coloration signals the ability to cope with elevated stress hormones: effects of corticosterone on growth of barn owls are associated with melanism.

Stressful situations during development can shape the phenotype for life by provoking a trade‐off between development and survival. Stress hormones, mainly glucocorticoids, play an important orchestrating role in this trade‐off. Hence, how stress sensitive an animal is critically determines the phenotype and ultimately fitness. In several species, darker eumelanic individuals are less sensitive to stressful conditions than less eumelanic conspecifics, which may be due to the pleiotropic effects of genes affecting both coloration and physiological traits. We experimentally tested whether the degree of melanin‐based coloration is associated with the sensitivity to an endocrine response to stressful situations in the barn owl. We artificially administered the mediator of a hormonal stress response, corticosterone, to nestlings to examine the prediction that corticosterone‐induced reduction in growth rate is more pronounced in light eumelanic nestlings than in darker nest mates. To examine whether such an effect may be genetically determined, we swapped hatchlings between randomly chosen pairs of nests. We first showed that corticosterone affects growth and, thus, shapes the phenotype. Second, we found that under corticosterone administration, nestlings with large black spots grew better than nestlings with small black spots. As in the barn owl the expression of eumelanin‐based coloration is heritable and not sensitive to environmental conditions, it is therefore a reliable, genetically based sign of the ability to cope with an increase in blood corticosterone level.

Equal nonbreeding period survival in adults and juveniles of a long‐distant migrant bird

In migrant birds, survival estimates for the different life-history stages between fledging and first breeding are scarce. First-year survival is shown to be strongly reduced compared with annual survival of adult birds. However, it remains unclear whether the main bottleneck in juvenile long-distant migrants occurs in the postfledging period within the breeding ranges or en route. Quantifying survival rates during different life-history stages and during different periods of the migration cycle is crucial to understand forces driving the evolution of optimal life histories in migrant birds. Here, we estimate survival rates of adult and juvenile barn swallows (Hirundo rusticaL.) in the breeding and nonbreeding areas using a population model integrating survival estimates in the breeding ranges based on a large radio-telemetry data set and published estimates of demographic parameters from large-scale population-monitoring projects across Switzerland. Input parameters included the country-wide population trend, annual productivity estimates of the double-brooded species, and year-to-year survival corrected for breeding dispersal. Juvenile survival in the 3-week postfledging period was low (S = 0.32; SE = 0.05), whereas in the rest of the annual cycle survival estimates of adults and juveniles were similarly high (S > 0.957). Thus, the postfledging period was the main survival bottleneck, revealing the striking result that nonbreeding period mortality (including migration) is not higher for juveniles than for adult birds. Therefore, focusing future research on sources of variation in postfledging mortality can provide new insights into determinants of population dynamics and life-history evolution of migrant birds.

Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models

Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.

The earth is flat (p>0.05): Significance thresholds and the crisis of unreplicable research

The widespread use of ‘statistical significance’ as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into ‘significant’ and ‘nonsignificant’ contributes to making studies irreproducible, or to making them seem irreproducible. A major problem is that we tend to take small p-values at face value, but mistrust results with larger p-values. In either case, p-values tell little about reliability of research, because they are hardly replicable even if an alternative hypothesis is true. Also significance (p ≤ 0.05) is hardly replicable: at a good statistical power of 80%, two studies will be ‘conflicting’, meaning that one is significant and the other is not, in one third of the cases if there is a true effect. A replication can therefore not be interpreted as having failed only because it is nonsignificant. Many apparent replication failures may thus reflect faulty judgment based on significance thresholds rather than a crisis of unreplicable research. Reliable conclusions on replicability and practical importance of a finding can only be drawn using cumulative evidence from multiple independent studies. However, applying significance thresholds makes cumulative knowledge unreliable. One reason is that with anything but ideal statistical power, significant effect sizes will be biased upwards. Interpreting inflated significant results while ignoring nonsignificant results will thus lead to wrong conclusions. But current incentives to hunt for significance lead to selective reporting and to publication bias against nonsignificant findings. Data dredging, p-hacking, and publication bias should be addressed by removing fixed significance thresholds. Consistent with the recommendations of the late Ronald Fisher, p-values should be interpreted as graded measures of the strength of evidence against the null hypothesis. Also larger p-values offer some evidence against the null hypothesis, and they cannot be interpreted as supporting the null hypothesis, falsely concluding that ‘there is no effect’. Information on possible true effect sizes that are compatible with the data must be obtained from the point estimate, e.g., from a sample average, and from the interval estimate, such as a confidence interval. We review how confusion about interpretation of larger p-values can be traced back to historical disputes among the founders of modern statistics. We further discuss potential arguments against removing significance thresholds, for example that decision rules should rather be more stringent, that sample sizes could decrease, or that p-values should better be completely abandoned. We conclude that whatever method of statistical inference we use, dichotomous threshold thinking must give way to non-automated informed judgment.

Large‐scale spatial analysis of ringing and re‐encounter data to infer movement patterns: A review including methodological perspectives

Summary A major aim of bird ringing is to provide information about the migration and movements of bird populations. However, in comparison with demographic studies, little research has been devoted to improving quantitative inferences through large-scale spatial analyses. This represents a serious knowledge gap because robust information on geographical linkages of migratory populations throughout the annual cycle is necessary to understand the ecology and evolution of migrants and for the conservation and management of populations. Here, we review recent developments and emerging opportunities for the quantitative study of movements of bird populations based on marked birds. Large-scale spatial analyses of ringing data need to account for spatiotemporal variation in re-encounter probability and the complexity of movement processes, including variability among individuals and populations in migration direction and distance. We identify seven recent studies that used quantitative methods for large-scale spatial analyses of ringing and re-encounter data gathered by national ringing centres. In most cases, numbers ringed and recovered in a series of source and destination areas were used to derive estimates of the proportion of each source population travelling to each destination area. Where recovery data were sparse, precision was improved by incorporating information on re-encounter probabilities of similar species. When numbers ringed were not available, inferences could sometimes be drawn based on local recapture data from the source areas. Studies to date illustrate that analyses of these large-scale ringing data sets can provide robust quantitative inferences. Further work is needed to develop these modelling approaches and to test their sensitivity to key assumptions using both real and simulated data. Data for all birds that were marked, not only those re-encountered, are often inaccessible and should be computerised in parallel with analytical developments. Further, there is great potential for the formal combination of re-encounter data with information from additional data sources such as counts and detailed movement data from radiotracking or data loggers. Because data from bird ringing operations cover long periods of time and exist in large quantities, they hold great promise for inferring spatiotemporal migration patterns, including changes in relation to climate, land use change and other environmental drivers.

Mortality estimation from carcass searches using the R-package carcass - a tutorial

This article is a tutorial for the R-package carcass. It starts with a short overview of common methods used to estimate mortality based on carcass searches. Then, it guides step by step through a simple example. First, the proportion of animals that fall into the search area is estimated. Second, carcass persistence time is estimated based on experimental data. Third, searcher efficiency is estimated. Fourth, these three estimated parameters are combined to obtain the probability that an animal killed is found by an observer. Finally, this probability is used together with the observed number of carcasses found to obtain an estimate for the total number of killed animals together with a credible interval.

Migratory connectivity derived from sparse ring reencounter data with unknown numbers of ringed birds

AbstractThe large databases on ring reencounters, e.g. Euring database, contain extant information on the spatial distribution and potentially, on migratory connectivity of birds. However, reencounter data are normally sparse due to low reencounter probability. Further, to extract unbiased information about the spatial distribution of birds, spatial variation in reencounter probability has to be corrected for. To do so, knowledge of the total numbers of ringed birds is crucial but often not available. We present a general, combined statistical model to estimate population specific migration patterns based on the European reencounter data for which the number of ringed birds is unknown. Our approach combines a Cormack–Jolly–Seber model with a multinomial model. We present, for the first time, estimates and credible intervals of the spatial distribution of different populations of a migrant bird during the non-breeding period based on imperfect ringing data. Here, we used the Common Nightingale (Luscinia megarhynchos) as a representative long-distance migrant. The model allowed estimation of which proportions of the different breeding populations use a western, central or eastern flyway. Sensitivity analysis based on simulated data showed that most of these estimates were robust against violation of the most important model assumptions, i.e. homogeneity in recapture probability, homogeneity in breeding area return probability, and in reencounter probability within the flyways. We provide a general technique to account for spatial variation in reencounter probability when analysing migratory connectivity based on ring reencounter data with unknown numbers of ringed individuals. It is applicable for almost all migrating species with reencounter data.ZusammenfassungAbleitung der Zug-Konnektivität zwischen Brut- und Nichtbrutgebiet aus spärlichen Ringwiederfunddaten und unbekannter Gesamtzahl beringter Individuen Umfassende Ringfunddatenbanken, wie die Euring-Datenbank, enthalten wertvolle Information über die räumliche Verteilung von Zugvögeln und potentiell zur Verbindungsstärke zwischen Brut- und Nichtbrutgebiet (Zug-Konnektivität). Wegen geringer Ringfundwahrscheinlichkeiten ist die Stichprobengrösse von Ringfunddaten jedoch oft klein. Wenn die räumliche Verteilung der Vögel basierend auf Ringwiederfunddaten beschrieben werden soll, muss eine räumliche Heterogenität der Ringfundwahrscheinlichkeit berücksichtigt werden. Um die Ringfundwahrscheinlichkeit schätzen zu können, sollte die Gesamtzahl beringter Vögel bekannt sein. Diese Anzahl ist jedoch in den meisten Ringfunddatenbanken nicht oder nicht detailliert enthalten. Wir stellen hier ein statistisches Modell vor, das populationsspezifische Zugmuster basierend auf den europäischen Ringfunddaten mit unbekannter Anzahl beringter Vögel zu schätzen erlaubt. Unser Ansatz beinhaltet eine Kombination eines Cormack-Jolly-Seber Modells zur Schätzung der Zahl zur Brutzeit beringter Vögel, mit einem multinominalen Modell zur Beschreibung der räumlichen Verteilung der Vögel ausserhalb der Brutzeit. Am Beispiel der Nachtigall (Luscinia megarhynchos) als typischer Langstreckenzieher präsentieren wir erstmalig Schätzwerte und Vertrauensintervalle für die räumliche Verteilung der Individuen verschiedener Populationen ausserhalb der Brutzeit, die auf nicht standardisierten Ringfunddaten basieren. Eine nachfolgende Sensitivitätsanalyse zeigte, dass die meisten Modellschätzwerte robust gegenüber Verletzungen der Modellannahmen zu homogenen Wiederfangwahrscheinlichkeiten im Brutgebiet, homogener Rückkehrrate ins Brutgebiet und homogener Wiederfundwahrscheinlichkeiten innerhalb eines Zugweges waren.

Temperature characteristics of winter roost-sites for birds and mammals: tree cavities and anthropogenic alternatives.

The microclimate of potential roost-sites is likely to be a crucial determinant in the optimal roost-site selection of endotherms, in particular during the winter season of temperate zones. Available roost-sites for birds and mammals in European high trunk orchards are mainly tree cavities, wood stacks and artificial nest boxes. However, little is known about the microclimatic patterns inside cavities and thermal advantages of using these winter roost-sites. Here, we simultaneously investigate the thermal patterns of winter roost-sites in relation to winter ambient temperature and their insulation capacity. While tree cavities and wood stacks strongly buffered the daily cycle of temperature changes, nest boxes showed low buffering capacity. The buffering effect of tree cavities was stronger at extreme ambient temperatures compared to temperatures around zero. Heat sources inside roosts amplified Δ T (i.e., the difference between inside and outside temperatures), particularly in the closed roosts of nest boxes and tree cavities, and less in the open wood stacks with stronger circulation of air. Positive Δ T due to the installation of a heat source increased in cold ambient temperatures. These results suggest that orchard habitats in winter show a spatiotemporal mosaic of sites providing different thermal benefits varying over time and in relation to ambient temperatures. At cold temperatures tree cavities provide significantly higher thermal benefits than nest boxes or wood stacks. Thus, in winter ecology of hole-using endotherms, the availability of tree cavities may be an important characteristic of winter habitat quality.

Estimates from non‐replicated population surveys rely on critical assumptions

Summary N-mixture and occupancy models are often used to account for non-detections in population surveys. The consensus has been that the methods require data that are replicated in space, as well as within a short period of time while the population at each site remains closed, in order for parameters such as detection probabilities and expected abundances to be identifiable. The requirement of replication prohibits the use of N-mixture and occupancy models for many surveys in practice. Recently, some studies have argued that N-mixture and occupancy models for surveys with only one visit at each site are identifiable when covariates for both detection probabilities and expected abundances, with at least one distinct covariate for each, are available (Journal of Plant Ecology, 5, 2012, 22; Environmetrics, 23, 2012, 197). We investigate the reasons for why detection probabilities have traditionally been considered unestimable from non-replicated counts and how the new methods sidestep these issues. We further use simulations to investigate properties of the new estimators. We show that detection probabilities of the single-visit models with covariates are non-identifiable and that absolute abundances cannot be estimated when particular link functions are employed (log links for both expected abundance and detection probability). Further, assumptions about the range within which detection probabilities vary are necessary to render estimability. The possibility of estimating abundance from single-visit surveys therefore implicitly hinges on knowledge about the link functions. Simulations show that estimates of abundance can be highly variable and sensitive to the choice of link function. We further show how a reduced parameterization of an N-mixture model for surveys repeated over time, without replication under closure but where detection probabilities are constant over time, corresponds to a Poisson model. Non-robust estimation can result in misleading conclusions about population abundance. When estimating abundance from count data that are not replicated, it is therefore important to be aware of how imprecise estimators may be and how sensitive they are to model assumptions.