Untersuchung der mentalen Repräsentation von Energiemanagement bei der Flugzeugführung zur Entwicklung eines Pilotenassistenzsystems

Um die mentale Repräsentation des Energiemanagements bei der manuellen Flugzeugführung zu untersuchen, wurde eine Simulatorkampagne mit n = 12 lizenzierten Verkehrspiloten durchgeführt. Ihre Aufgabe war es, künstlich generierte Höhen- und Geschwindigkeitsablagen auf dem Gleitpfad des Instrumentenlandesystems (ILS) im Endanflug zu korrigieren. Dabei wurde untersucht, ob und inwiefern sie von dem Prinzip des Energieaustauschs Gebrauch machen. Die Ergebnisse zeigen eine wenig einheitlich ausgeprägte Repräsentation des Wissens bezüglich des Energiemanagements. Des Weiteren war zu erkennen, dass nicht die vollen Möglichkeiten des Energieaustausches genutzt wurden. Vielmehr wurden damit lediglich kleine Korrekturen durchgeführt

A Triple-Isotope Approach to Predict the Breeding Origins of European Bats

Despite a commitment by the European Union to protect its migratory bat populations, conservation efforts are hindered by a poor understanding of bat migratory strategies and connectivity between breeding and wintering grounds. Traditional methods like mark-recapture are ineffective to study broad-scale bat migratory patterns. Stable hydrogen isotopes (δD) have been proven useful in establishing spatial migratory connectivity of animal populations. Before applying this tool, the method was calibrated using bat samples of known origin. Here we established the potential of δD as a robust geographical tracer of breeding origins of European bats by measuring δD in hair of five sedentary bat species from 45 locations throughout Europe. The δD of bat hair strongly correlated with well-established spatial isotopic patterns in mean annual precipitation in Europe, and therefore was highly correlated with latitude. We calculated a linear mixed-effects model, with species as random effect, linking δD of bat hair to precipitation δD of the areas of hair growth. This model can be used to predict breeding origins of European migrating bats. We used δ13C and δ15N to discriminate among potential origins of bats, and found that these isotopes can be used as variables to further refine origin predictions. A triple-isotope approach could thereby pinpoint populations or subpopulations that have distinct origins. Our results further corroborated stable isotope analysis as a powerful method to delineate animal migrations in Europe

Appendix A. Tables showing alphabetical lists of bat species (with varying feeding habits) captured at La Selva Biological Station, Costa Rica, with corresponding ratios of non-exchangeable hydrogen stable isotopes in fur keratin and of hydrogen stable isotopes in body water from field season A, and corresponding ratios of non-exchangeable hydrogen stable isotopes and nitrogen isotopes in hair keratin from field season B.

Tables showing alphabetical lists of bat species (with varying feeding habits) captured at La Selva Biological Station, Costa Rica, with corresponding ratios of non-exchangeable hydrogen stable isotopes in fur keratin and of hydrogen stable isotopes in body water from field season A, and corresponding ratios of non-exchangeable hydrogen stable isotopes and nitrogen isotopes in hair keratin from field season B

Results of the linear mixed-effects model fit by REML (model b) for predicting δD_h from latitude, longitude and elevation, with species as random intercept.

<p>Number of observations: 178. Number of groups (random effect species): 5. AIC = 1444.34, BIC = 1475.69, logLik −712.17. The random intercept was normally distributed (mean 0, SD 5.62), and so was its residual term (mean 0, SD 9.38). Model residuals were normally distributed (Lilliefors D = 0.0403, <i>P</i> = 0.1732).</p>2<p>: variable included as quadratic term.</p

Results of the linear mixed-effects model fit by reduced maximum likelihood (REML; model a1 in Table 2) for predicting δD_h from δD_p, with species as random intercept.

<p>Number of observations: 178. Number of groups (random effect species): 5. AIC = 1331.97, BIC = 1334.65, logLik −666.98. The random intercept was normally distributed, with mean 0 and standard deviation (SD) 2.54, and so was its residual term, with mean 0 and SD 9.85. Model residuals were normally distributed (Lilliefors D = 0.0266, <i>P</i> = 0.7844).</p

Site locations of bat hair samples.

<p>Circles are filled in according to the species or genus at that site: <i>Eptesicus serotinus</i>/<i>E. isabellinus</i>, open circles; <i>Barbastella barbastellus</i>, grey circles; <i>Plecotus auritus</i>/<i>P. austriacus</i>, black circles. Proximate sampling sites were grouped as one circle for clarity. Numbers refer to sites in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030388#pone.0030388.s003" target="_blank">Table S1</a>.</p

Correlation between δD of bat hair (δD_h) and δD of mean annual (δD_p) precipitation.

<p>Regression (line), 95% confidence intervals (dashed) and regression equation are given for the whole data set (n = 178). Empty circles: <i>E. serotinus/E. isabellinus</i>; black circles: <i>Plecotus auritus/P. austriacus</i>; grey circles: <i>Barbastella barbastellus</i>.</p

Multi-isotope triplet for <i>Eptesicus serotinus</i>/<i>E. isabellinus</i>.

<p>Circles represent values of <i>E. serotinus</i> samples, squares of <i>E. isabellinus</i>. Colors represent different sampling sites of hair. Yellow: 2; green: 3; pink: 6; blue: 14; red: 31 (numbers refer to sites in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030388#pone.0030388.s003" target="_blank">Table S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030388#pone-0030388-g001" target="_blank">Figure 1</a>).</p