Investigating the Impact of Observation Errors on the Statistical Performance of Network-based Diffusion Analysis

Experiments in captivity have provided evidence for social learning, but it remains challenging to demon- strate social learning in the wild. Recently, we developed network-based diffusion analysis (NBDA; 2009) as a new approach to inferring social learning from observational data. NBDA fits alternative models of asocial and social learning to the diffusion of a behavior through time, where the potential for social learning is related to a social network. Here, we investigate the performance of NBDA in relation to variation in group size, network heterogeneity, observer sampling errors, and duration of trait diffusion. We find that observation errors, when severe enough, can lead to increased Type I error rates in detecting social learning. However, elevated Type I error rates can be prevented by coding the observed times of trait acquisition into larger time units. Collectively, our results provide further guidance to applying NBDA and demonstrate that the method is more robust to sampling error than initially expected. Supplemental materials for this article may be downloaded from http:// lb.psychonomic-journals.org/content/supplemental.Human Evolutionary Biolog

Skill learning and the evolution of social learning mechanisms

This research was supported by a grant from The John Templeton Foundation.Background. Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. Results. We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. Conclusions. In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses.Publisher PDFPeer reviewe

The evolution of cooperative turn-taking in animal conflict

<p>Abstract</p> <p>Background</p> <p>A fundamental assumption in animal socio-ecology is that animals compete over limited resources. This view has been challenged by the finding that individuals might cooperatively partition resources by "taking turns". Turn-taking occurs when two individuals coordinate their agonistic behaviour in a way that leads to an alternating pattern in who obtains a resource without engaging in costly fights. Cooperative turn-taking has been largely ignored in models of animal conflict and socio-ecological models that explain the evolution of social behaviours based only on contest and scramble competition. Currently it is unclear whether turn-taking should be included in socio-ecological models because the evolution of turn-taking is not well understood. In particular, it is unknown whether turn-taking can evolve when fighting costs and assessment of fighting abilities are not fixed but emerge from evolved within-fight behaviour. We address this problem with an evolutionary agent-based model.</p> <p>Results</p> <p>We found that turn-taking evolves for small resource values, alongside a contest strategy that leads to stable dominance relationships. Turn-taking leads to egalitarian societies with unclear dominance relationships and non-linear dominance hierarchies. Evolutionary stability of turn-taking emerged despite strength differences among individuals and the possibility to evolve within-fight behaviour that allows good assessment of fighting abilities. Evolutionary stability emerged from frequency-dependent effects on fitness, which are modulated by feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies.</p> <p>Conclusions</p> <p>Our results reveal the impact of feedbacks between the evolution of within-fight behaviour and the evolution of higher-level conflict strategies, such as turn-taking. Similar feedbacks might be important for the evolution of other conflict strategies such as winner-loser effects or coalitions. However, we are not aware of any study that investigated such feedbacks. Furthermore, our model suggests that turn-taking could be used by animals to partition low value resources, but to our knowledge this has never been tested. The existence of turn-taking might have been overlooked because it leads to societies with similar characteristics that have been expected to emerge from scramble competition. Analyses of temporal interaction patterns could be used to test whether turn-taking occurs in animals.</p

Multi-Scale Variability Analysis of Wheat Straw-Based Ethanol Biorefineries Identifies Bioprocess Designs Robust Against Process Input Variations

Bioprocesses based on (ligno-)cellulosic biomass are highly prone to batch-to-batch variations. Varying raw material compositions and enzyme activities hamper the prediction of process yields, economic feasibility and environmental impacts. Commonly, these performance indicators are averaged over several experiments to select suitable process designs. The variabilities in performance indicators resulting from variable process inputs are often neglected, causing a risk for faulty performance predictions and poor process design choices during scale-up. In this paper, a multi-scale variability analysis framework is presented that quantifies the effects of process input variations on performance indicators. Using the framework, a kinetic model describing simultaneous saccharification and ethanol fermentation was integrated with a flowsheet process model, techno-economic analysis and life cycle assessment in order to evaluate a wheat straw-based ethanol biorefinery. Hydrolytic activities reported in the literature for the enzyme cocktail Cellic\uae CTec2, ranging from 62 to 266 FPU\ub7mL−1, were used as inputs to the multi-scale model to compare the variability in performance indicators under batch and multi-feed operation for simultaneous saccharification and fermentation. Bioprocess simulations were stopped at ethanol productivities ≤0.1 g\ub7L−1\ub7h−1. The resulting spreads in process times, hydrolysis yields, and fermentation yields were incorporated into flowsheet, techno-economic and life cycle scales. At median enzymatic activities the payback time was 7%, equal to 0.6 years, shorter under multi-feed conditions. All other performance indicators showed insignificant differences. However, batch operation is simpler to control and well-established in industry. Thus, an analysis at median conditions might favor batch conditions despite the disadvantage in payback time. Contrary to median conditions, analyzing the input variability favored multi-feed operation due to a lower variability in all performance indicators. Variabilities in performance indicators were at least 50% lower under multi-feed operation. Counteracting the variability in enzymatic activities by adjusting the amount of added enzyme instead resulted in higher uncertainties in environmental impacts. The results show that the robustness of performance indicators against input variations must be considered during process development. Based on the multi-scale variability analysis process designs can be selected which deliver more precise performance indicators at multiple system levels

Magnetic microstructure and magnetotransport in Co2FeAl Heusler compound thin films

We correlate simultaneously recorded magnetotransport and spatially resolved magneto optical Kerr effect (MOKE) data in Co2FeAl Heusler compound thin films micropatterned into Hall bars. Room temperature MOKE images reveal the nucleation and propagation of domains in an externally applied magnetic field and are used to extract a macrospin corresponding to the mean magnetization direction in the Hall bar. The anisotropic magnetoresistance calculated using this macrospin is in excellent agreement with magnetoresistance measurements. This suggests that the magnetotransport in Heusler compounds can be adequately simulated using simple macrospin models, while the magnetoresistance contribution due to domain walls is of negligible importance

Quality Assessment of Imputations in Administrative Data

This article contributes a framework for the quality assessment of imputations within a broader structure to evaluate the quality of register-based data. Four quality-related hyperdimensions examine the data processing from the raw-data level to the final statistics. Our focus lies on the quality assessment of different imputation steps and their influence on overall data quality. We suggest classification rates as a measure of accuracy of imputation and derive several computational approaches. (authors' abstract

Recruitment and monitoring behaviors by leaders predict following in wild Barbary macaques (Macaca sylvanus)

For group-living animals it is essential to maintain the cohesiveness of the group when traveling. Individuals have to make an accurate decision about where and when to move. Communication before and during the departure of the first individual may play a crucial role in synchronizing a collective movement. We hypothesized that individuals in a wild primate group use signals or cues prior to and after departure to achieve collective movements. With two observers we used all-occurrences behavior sampling of collective movements in a group of wild Barbary macaques (Macaca sylvanus) in the Middle Atlas, Morocco. The number of individuals displaying pre-departure behavior predicted the success of an initiation of a collective movement. Pauses of the first departing individual after departure enhanced following behavior and might have served as recruitment signal. However, the opposite was the case for back-glancing, which functions as a monitoring signal in other species. Because in our study frequently back-glancing individuals were also less socially integrated, back glances may better be interpreted as indicators of hesitation and insecurity. To successfully initiate a collective movement, it seemed to be sufficient for a socially integrated group member to take action when other group members signal their willingness prior to departure and to occasionally wait for the group while movin

Comparison of spectral indices to detect nitrogen uptake in winter wheat

Die vorliegende Arbeit beschäftigte sich mit dem Einsatz von Spektralsensoren unter Verwendung von Spektral­indices zur gezielten Erfassung der Stickstoffaufnahme bei Winterweizen (Triticum aestivum). Ziel war es, die Güte und die Genauigkeit bekannter Vegetationsindices zu quantifizieren und diese zu vergleichen. Darüber hinaus wurden für den Wellenlängenbereich 400 bis 900 nm in 2,8 nm-Schritten alle möglichen Zwei-Band-Indices errechnet und anhand von Korrelationsmatrizen deren Güte als Indikator für die Stickstoffversorgung beurteilt. Zu den Terminen EC 32, EC 39 und EC 65 wurden Spektralmessungen durchgeführt und anschließend ausgewertet. Zur Beurteilung der Qualität der Indices wurden parallel zu den Spektralmessungen destruktive Datenerhebungen an Pflanzenbeständen im Winterweizen durchgeführt. Zwischen der N-Aufnahme und den Indices PLSR, YARA_ALS und REIP_700 errechneten sich Bestimmtheitsmaße (R2) von bis zu 0,9. Neben den R2-Werten wurde außerdem die Sättigung, also die Veränderung der Messwerte gegenüber der divergierenden Stickstoffaufnahme der Pflanzen ermittelt. Als Vegetationsindices mit besonders hoher Sättigung erwiesen sich der NDVI und der SAVI.The present work deals with the use of spectral sensors with spectral indices for the targeted detection of nitrogen uptake in winter wheat (Triticum aestivum). The aim was to quantify and compare the quality and accuracy of known vegetation indices. In addition, for the wavelength range 400 to 900 nm in 2.8 nm steps, all possible two-band indices were calculated and their quality was evaluated as an indicator for the nitrogen supply by means of correlation matrices. The spectral measurements were carried out at defined measurement data for EC 32, EC 39 and EC 65 and then evaluated. In order to assess the quality of the indices, destructive data collections on plant populations in winter wheat were carried out parallel to the spectral measurements. Between the N-record and the indices PLSR, YARA_ALS and REIP_700, coefficients of determination (R2) of up to 0.9 were calculated. In addition to the R2 values, the saturation, i.e. the change in the measured values in comparison to the divergent nitrogen uptake of the plants, was also determined. Particularly high saturating vegetation indices were the NDVI and the SAVI