Temporal Changes in Randomness of Bird Communities across Central Europe

Many studies have examined whether communities are structured by random or deterministic processes, and both are likely to play a role, but relatively few studies have attempted to quantify the degree of randomness in species composition. We quantified, for the first time, the degree of randomness in forest bird communities based on an analysis of spatial autocorrelation in three regions of Germany. The compositional dissimilarity between pairs of forest patches was regressed against the distance between them. We then calculated the y-intercept of the curve, i.e. the ‘nugget’, which represents the compositional dissimilarity at zero spatial distance. We therefore assume, following similar work on plant communities, that this represents the degree of randomness in species composition. We then analysed how the degree of randomness in community composition varied over time and with forest management intensity, which we expected to reduce the importance of random processes by increasing the strength of environmental drivers. We found that a high portion of the bird community composition could be explained by chance (overall mean of 0.63), implying that most of the variation in local bird community composition is driven by stochastic processes. Forest management intensity did not consistently affect the mean degree of randomness in community composition, perhaps because the bird communities were relatively insensitive to management intensity. We found a high temporal variation in the degree of randomness, which may indicate temporal variation in assembly processes and in the importance of key environmental drivers. We conclude that the degree of randomness in community composition should be considered in bird community studies, and the high values we find may indicate that bird community composition is relatively hard to predict at the regional scale.

Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.

Optical quantum random number generator

A physical random number generator based on the intrinsic randomness of quantum mechanics is described. The random events are realized by the choice of single photons between the two outputs of a beamsplitter. We present a simple device, which minimizes the impact of the photon counters’ noise, dead-time and after pulses.

Why Monte Carlo Simulations are Inferences and not Experiments

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

Decision-Making Processes in Voluntary Football Clubs in Relation to External Counselling

Introduction Recruiting and retaining volunteers who are prepared to make a long-term commitment is a major problem for Swiss sports clubs. With the inclusion of external counselling for the change and systematisation of volunteer management, sports clubs have a possibility to develop and defuse problems in spite of existing barriers and gaps in knowledge. To what extent is external counselling for personnel problems effective? It is often observed that standardised counselling inputs lead to varying consequences for sports clubs. It can be assumed that external impulses are interpreted and transformed differently into the workings of the club. However, this cannot be solely attributed to the situational or structural conditions of the clubs. It is also important to consider the underlying decision-making processes of a club. According to Luhmann’s organisational sociological considerations (2000), organisations (sports clubs) have to be viewed as social systems consisting of (communicated) decisions. This means that organisations are continually reproduced by decision-making processes. All other (observable) factors such as an organisation’s goals, recruiting strategies, support schemes for volunteers etc., have to be seen as an outcome of the operation of prior organisational decisions. Therefore: How do decision-making processes in sports clubs work in the context of the implementation of external counselling? Theoretical Framework An examination of the actual situation in sports clubs shows that decisions frequently appear to be shaped by inconsistency, unexpected outcomes, and randomness (Amis & Slack, 2003). Therefore, it must be emphasised that these decisions cannot be analysed according to any rational decision-making model. Their specific structural characteristics only permit a limited degree of rationality – bounded rationality. Non-profit organisations in particular are shaped by a specific mode of decisionmaking that Cohen, March, and Olsen (1972) have called the “garbage can model”. As sport clubs can also be conceived as “organised anarchies”, this model seems to offer an appropriate approach to understanding their practices and analysing their decision-making processes. The key concept in the garbage can model is the assumption that decision-making processes in organisations consist of four “streams”: (a) problems, (b) actors, (c) decision-making opportunities, and (d) solutions. Method Before presenting the method of the analysis of the decision-making processes in sports clubs, the external counselling will be described. The basis of the counselling is generated by a sports clubs’ capability to change. Due to the specific structural characteristics and organisational principles, change processes in sports clubs often merge with barriers and restrictions. These need to be considered when developing counselling guidelines for a successful planning and realisation of change processes. Furthermore, important aspects of personnel management in sports clubs and especially volunteer management must be implied in order to elaborate key elements for the counselling to recruit new volunteers (e.g., approach, expectations). A counselling of four system-counselling workshops was conceptualised by considering these specific characteristics. The decision-making processes in the sports clubs were analysed during the counselling and the implementation process. A case study is designed with the appropriate methodological approach for such explorative research. The approach adopted for these single case analyses was oriented toward the research program of behavioural decision-making theory (garbage can model). This posits that in-depth insights into organisational decision-making processes can only be gained through relevant case studies of existing organisational situations (Skille, 2013). Before, during and after the intervention, questionnaires and guided interviews were conducted with the project teams of the twelve par-ticipating football clubs to assess the different components of the “streams” in the context of external counselling. These interviews have been analysed using content analysis following guidelines as for-mulated by Mayring (2010). Results The findings show that decision-making processes in football clubs occur differently in the context of external counselling. Different initial positions and problems are the triggers for these decision-making processes. Furthermore, the implementation of the solutions and the external counselling is highly dependent on the commitment of certain people as central players within the decision-mak-ing process. The importance of these relationships is confirmed by previous findings in regard to decision-making and change processes in sports clubs. The decision-making processes in sports clubs can be theoretically analysed using behavioural decision-making theory and the “garbage can model”. Bounded rationality characterises all “streams” of the decision-making processes. Moreo-ver, the decision-making process of the football clubs can be well illustrated in the framework, and the interplay of the different dimensions illustrates the different decision-making practices within the football clubs. References Amis, J., & Slack, T. (2003). Analysing sports organisations: Theory and practice. In B. Houlihan (Eds.), Sport & Society (pp. 201–217). London, England: Sage. Cohen, M.D., March, J.G., & Olsen, J.P. (1972). A garbage can model of organisational choice. Ad-ministrative Science Quarterly, 17, 1-25. Luhmann, N. (2000). Organisation und Entscheidung. Opladen: Westdeutscher Verlag. Mayring, P. (2010). Qualitative Inhaltsanalyse. Grundlagen und Techniken. Weinheim: Beltz. Skille, E. Å. (2013). Case study research in sport management: A reflection upon the theory of science and an empirical example. In S. Söderman & H. Dolles (Eds.), Handbook of research on sport and business (pp. 161–175). Cheltenham, England: Edward Elgar.

Cloud observations in Switzerland using hemispherical sky cameras

We present observations of total cloud cover and cloud type classification results from a sky camera network comprising four stations in Switzerland. In a comprehensive intercomparison study, records of total cloud cover from the sky camera, long-wave radiation observations, Meteosat, ceilometer, and visual observations were compared. Total cloud cover from the sky camera was in 65–85% of cases within ±1 okta with respect to the other methods. The sky camera overestimates cloudiness with respect to the other automatic techniques on average by up to 1.1 ± 2.8 oktas but underestimates it by 0.8 ± 1.9 oktas compared to the human observer. However, the bias depends on the cloudiness and therefore needs to be considered when records from various observational techniques are being homogenized. Cloud type classification was conducted using the k-Nearest Neighbor classifier in combination with a set of color and textural features. In addition, a radiative feature was introduced which improved the discrimination by up to 10%. The performance of the algorithm mainly depends on the atmospheric conditions, site-specific characteristics, the randomness of the selected images, and possible visual misclassifications: The mean success rate was 80–90% when the image only contained a single cloud class but dropped to 50–70% if the test images were completely randomly selected and multiple cloud classes occurred in the images.