The resurrection of group selection as a theory of human cooperation

Two books edited by members of the MacArthur Norms and Preferences Network (an interdisciplinary group, mainly anthropologists and economists) are reviewed here. These books in large part reflect a renewed interest in group selection that has occurred among these researchers: they promote the theory that human cooperative behavior evolved via selective processes which favored biological and/or cultural group-level adaptations as opposed to individual-level adaptations. In support of this theory, an impressive collection of cross-cultural data are presented which suggest that participants in experimental economic games often do not behave as self-interested income maximizers; this lack of self-interest is regarded as evidence of group selection. In this review, problems with these data and with the theory are discussed. On the data side, it is argued that even if a behavior seems individually-maladaptive in a game context, there is no reason to believe that it would have been that way in ancestral contexts, since the environments of experimental games do not at all resemble those in which ancestral humans would have interacted cooperatively. And on the theory side, it is argued that it is premature to invoke group selection in order to explain human cooperation, because more parsimonious individual-level theories have not yet been exhausted. In summary, these books represent ambitious interdisciplinary contributions on an important topic, and they include unique and useful data; however, they do not make a convincing case that the evolution of human cooperation required group selection

Design definition study of a NASA/Navy lift/cruise fan technology V/STOL airplane: Risk assessment addendum to the final report

An assessment of risk, in terms of delivery delays, cost overrun, and performance achievement, associated with the V/STOL technology airplane is presented. The risk is discussed in terms of weight, structure, aerodynamics, propulsion, mechanical drive, and flight controls. The analysis ensures that risks associated with the design and development of the airplane will be eliminated in the course of the program and a useful technology airplane that meets the predicted cost, schedule, and performance can be produced

Winter Conditions Influence Biological Responses of Migrating Hummingbirds

Conserving biological diversity given ongoing environmental changes requires the knowledge of how organisms respond biologically to these changes; however, we rarely have this information. This data deficiency can be addressed with coordinated monitoring programs that provide field data across temporal and spatial scales and with process-based models, which provide a method for predicting how species, in particular migrating species that face different conditions across their range, will respond to climate change. We evaluate whether environmental conditions in the wintering grounds of broad-tailed hummingbirds influence physiological and behavioral attributes of their migration. To quantify winter ground conditions, we used operative temperature as a proxy for physiological constraint, and precipitation and the normalized difference vegetation index (NDVI) as surrogates of resource availability. We measured four biological response variables: molt stage, timing of arrival at stopover sites, body mass, and fat. Consistent with our predictions, we found that birds migrating north were in earlier stages of molt and arrived at stopover sites later when NDVI was low. These results indicate that wintering conditions impact the timing and condition of birds as they migrate north. In addition, our results suggest that biologically informed environmental surrogates provide a valuable tool for predicting how climate variability across years influences the animal populations

Intention of preserving forest remnants among landowners in the Atlantic Forest: The role of the ecological context via ecosystem services

Unravelling the psychological processes determining landowners' support towards forest conservation is crucial, particularly in rural areas of the tropics, where most forest remnants are within private lands. As human–nature connections are known to shape pro‐environmental behaviours, the intention of preserving forest remnants should ultimately be determined by the ecological context people live in. Here, we investigate the pathways through which the ecological context (forest cover), via direct contact with forests and ecosystem services and disservices, influence the psychological antecedents of conservation behaviour (beliefs, attitude and intention of preserving forest remnants). We conceptualized a model based on the Reasoned Action Approach, using the ecological context and these three forest experiences as background factors, and tested the model using Piecewise Structural Equation Modelling. Data were collected through an interview‐based protocol applied to 106 landowners across 13 landscapes varying in forest cover in a consolidated rural region in the Brazilian Atlantic Forest. Our results indicate that: (a) ecosystem services are more important than disservices for shaping intention of preserving forests, particularly non‐provisioning services; (b) contact with forest has an indirect effect on intention, by positively influencing the frequency of receiving ecosystem services; (c) people living in more forested ecological contexts have more contact with forests, receive ecosystem services more frequently and, ultimately, have stronger intention of preserving forests. Hence, our study suggests a dangerous positive feedback loop between deforestation, the extinction of forest experiences and impairment of human–nature connections. Local demands across the full range of ecosystem services, the balance between services and disservices and the ecological context people live in should be considered when developing conservation initiatives in tropical rural areas

The Effect of Nonstationarity on Models Inferred from Neural Data

Neurons subject to a common non-stationary input may exhibit a correlated firing behavior. Correlations in the statistics of neural spike trains also arise as the effect of interaction between neurons. Here we show that these two situations can be distinguished, with machine learning techniques, provided the data are rich enough. In order to do this, we study the problem of inferring a kinetic Ising model, stationary or nonstationary, from the available data. We apply the inference procedure to two data sets: one from salamander retinal ganglion cells and the other from a realistic computational cortical network model. We show that many aspects of the concerted activity of the salamander retinal neurons can be traced simply to the external input. A model of non-interacting neurons subject to a non-stationary external field outperforms a model with stationary input with couplings between neurons, even accounting for the differences in the number of model parameters. When couplings are added to the non-stationary model, for the retinal data, little is gained: the inferred couplings are generally not significant. Likewise, the distribution of the sizes of sets of neurons that spike simultaneously and the frequency of spike patterns as function of their rank (Zipf plots) are well-explained by an independent-neuron model with time-dependent external input, and adding connections to such a model does not offer significant improvement. For the cortical model data, robust couplings, well correlated with the real connections, can be inferred using the non-stationary model. Adding connections to this model slightly improves the agreement with the data for the probability of synchronous spikes but hardly affects the Zipf plot.Comment: version in press in J Stat Mec

Evaluation of the BioFire FilmArray pneumonia panel for detection of viral and bacterial pathogens in lower respiratory tract specimens in the setting of a tertiary care academic medical center

Our objective was to evaluate the diagnostic yield and accuracy of the BioFire FilmArray pneumonia panel (BFPP) for identification of pathogens in lower respiratory tract specimens

A meta-BACI approach forevaluating management intervention on chronic wasting disease in mule deer

Advances in acquiring and analyzing the spatial attributes of data have greatlyenhanced the potential utility of wildlife disease surveillance data for addressing problems ofecological or economic importance. We present an approach for using wildlife diseasesurveillance data to identify areas for (or of ) intervention, to spatially delineate pairedtreatment and control areas, and then to analyze these nonrandomly selected sites in a meta-analysis framework via before–after–control–impact (BACI) estimates of effect size. We applythese methods to evaluate the effectiveness of attempts to reduce chronic wasting disease(CWD) prevalence through intensive localized culling of mule deer (Odocoileus hemionus)innorth-central Colorado, USA. Areas where surveillance data revealed high prevalence or caseclusters were targeted by state wildlife management agency personnel for focal scale (onaverage ,17 km2) culling, primarily via agency sharpshooters. Each area of sustained cullingthat we could also identify as unique by cluster analysis was considered a potential treatmentarea. Treatment areas, along with spatially paired control areas that we constructed post hocin a case-control design (collectively called ‘‘management evaluation sites’’), were thendelineated using home range estimators. Using meta-BACI analysis of CWD prevalence datafor all management evaluation sites, the mean effect size (change of prevalence on treatmentareas minus change in prevalence on their paired control areas) was 0.03 (SE ¼ 0.03); meaneffect size on treatment areas was not greater than on paired control areas. Excluding cullsamples from prevalence estimates or allowing for an equal or greater two-year lag in systemresponses to management did not change this outcome. We concluded that managementbenefits were not evident, although whether this represented true ineffectiveness or was a resultof lack of data or insufficient duration of treatment could not be discerned. Based on ourobservations, we offer recommendations for designing a management experiment with 80%power to detect a 0.10 drop in prevalence over a 6–12-year period

Fitting Ranked English and Spanish Letter Frequency Distribution in U.S. and Mexican Presidential Speeches

The limited range in its abscissa of ranked letter frequency distributions causes multiple functions to fit the observed distribution reasonably well. In order to critically compare various functions, we apply the statistical model selections on ten functions, using the texts of U.S. and Mexican presidential speeches in the last 1-2 centuries. Dispite minor switching of ranking order of certain letters during the temporal evolution for both datasets, the letter usage is generally stable. The best fitting function, judged by either least-square-error or by AIC/BIC model selection, is the Cocho/Beta function. We also use a novel method to discover clusters of letters by their observed-over-expected frequency ratios.Comment: 7 figure

Quantum Noise and Superluminal Propagation

Causal "superluminal" effects have recently been observed and discussed in various contexts. The question arises whether such effects could be observed with extremely weak pulses, and what would prevent the observation of an "optical tachyon." Aharonov, Reznik, and Stern (ARS) [Phys. Rev. Lett., vol. 81, 2190 (1998)] have argued that quantum noise will preclude the observation of a superluminal group velocity when the pulse consists of one or a few photons. In this paper we reconsider this question both in a general framework and in the specific example, suggested by Chiao, Kozhekin, and Kurizki [Phys. Rev. Lett., vol. 77, 1254 (1996)], of off-resonant, short-pulse propagation in an optical amplifier. We derive in the case of the amplifier a signal-to-noise ratio that is consistent with the general ARS conclusions when we impose their criteria for distinguishing between superluminal propagation and propagation at the speed c. However, results consistent with the semiclassical arguments of CKK are obtained if weaker criteria are imposed, in which case the signal can exceed the noise without being "exponentially large." We show that the quantum fluctuations of the field considered by ARS are closely related to superfluorescence noise. More generally we consider the implications of unitarity for superluminal propagation and quantum noise and study, in addition to the complete and truncated wavepackets considered by ARS, the residual wavepacket formed by their difference. This leads to the conclusion that the noise is mostly luminal and delayed with respect to the superluminal signal. In the limit of a very weak incident signal pulse, the superluminal signal will be dominated by the noise part, and the signal-to-noise ratio will therefore be very small.Comment: 30 pages, 1 figure, eps