Conformity in mate choice,the overlooked social component of animal and human culture

Although conformity as a major driver for human cultural evolution is a well-accepted and intensely studied phenomenon, its importance for non-human animal culture has been largely overlooked until recently. This limited for decades the possibility of studying the roots of human culture. Here, we provide a historical review of the study of conformity in both humans and non-human animals. We identify gaps in knowledge and propose an evolutionary route towards the sophisticated cultural processes that characterize humanity. A landmark in the study of conformity is Solomon Asch's famous experiment on humans in 1955. By contrast, interest in conformity among evolutionary biologists has only become salient since the turn of the new millennium. A striking result of our review is that, although studies of conformity have examined many biological contexts, only one looked at mate choice. This is surprising because mate choice is probably the only context in which conformity has self-reinforcing advantages across generations. Within a metapopulation, i.e. a group of subpopulations connected by dispersing individuals, dispersers able to conform to the local preference for a given type of mate have a strong and multigenerational fitness advantage. This is because once females within one subpopulation locally show a bias for one type of males, immigrant females who do not conform to the local trend have sons, grandsons, etc. of the non-preferred phenotype, which negatively and cumulatively affects fitness over generations in a process reminiscent of the Fisher runaway process. This led us to suggest a sex-driven origin of conformity, indicating a possible evolutionary route towards animal and human culture that is rooted in the basic, and thus ancient, social constraints acting on mating preferences within a metapopulation. In a generic model, we show that dispersal among subpopulations within a metapopulation can effectively maintain independent Fisher runaway processes within subpopulations, while favouring the evolution of social learning and conformity at the metapopulation scale; both being essential for the evolution of long-lasting local traditions. The proposed evolutionary route to social learning and conformity casts surprising light on one of the major processes that much later participated in making us human. We further highlight several research avenues to define the spectrum of conformity better, and to account for its complexity. Future studies of conformity should incorporate experimental manipulation of group majority. We also encourage the study of potential links between conformity and mate copying, animal aggregations, and collective actions. Moreover, validation of the sex-driven origin of conformity will rest on the capacity of human and evolutionary sciences to investigate jointly the origin of social learning and conformity. This constitutes a stimulating common agenda and militates for a rapprochement between these two currently largely independent research areas.     

Nonparametric and semiparametric estimation with sequentially truncated survival data

In observational cohort studies with complex sampling schemes, truncation arises when the time to event of interest is observed only when it falls below or exceeds another random time, that is, the truncation time. In more complex settings, observation may require a particular ordering of event times; we refer to this as sequential truncation. Estimators of the event time distribution have been developed for simple left-truncated or right-truncated data. However, these estimators may be inconsistent under sequential truncation. We propose nonparametric and semiparametric maximum likelihood estimators for the distribution of the event time of interest in the presence of sequential truncation, under two truncation models. We show the equivalence of an inverse probability weighted estimator and a product limit estimator under one of these models. We study the large sample properties of the proposed estimators and derive their asymptotic variance estimators. We evaluate the proposed methods through simulation studies and apply the methods to an Alzheimer's disease study. We have developed an R package, seqTrun , for implementation of our method.     

Differences in preference for species-specific female calls between acoustically experienced and acoustically naive maleRibautodelphax planthoppers (Homoptera: Delphacidae)

Males of the planthopper Ribautodelphax imitanswere exposed to playbacks of either conspecific or heterospecific (R. imitantoides)female calls during their development from egg to adult, and thereafter these, as well as naive males,were offered a two- way choice between these calls. Males of all treatments approached the conspecific call significantly more often. However, males primed by the conspecific call chose the heterospecific call almost four times less often than did males primed by heterospecific calls or naive males, thus showing that the preference for conspecific calls can be partly learned. Males primed by heterospecific calls performed very similarly to completely naive males, suggesting that the signal recognition mechanism is much less sensitive to heterospecific calls than to conspecific calls. Males with experience of the conspecific female call tended to take more time to reach the call source in the trials than both other types of males. The evolutionary implications of these findings are discussed.     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.     

Spatial sampling to detect slug abundance in an arable field

Overuse of molluscicides by farmers in arable systems can lead to environmental and product contamination. Here we assess a simple and inexpensive surface trapping method for monitoring populations of slugs (Deroceras reticulatum and Arion intermedius). This method was biased against small slugs, and against A. intermedius, when compared to direct soil sampling. Regression was used to model the relationship between the results of surface trapping and soil sampling methods. Spatial Analysis by Distance IndicEs (SADIE) algorithms were used to describe the spatial relationships between the two sets of samples. Using both traditional statistical methods and spatial statistics, the spatial information collected from surface traps was sufficient to identify patches and gaps in slug numbers and possibly to allow the spot application of slug control, and thus provide land managers who experience slug damage with a way of reducing molluscicides use, whilst maintaining slug control. Further improvements and applications of the model are discussed.     

Two-phase species–time relationships in North American land birds

The species–time relationship (STR) is a macroecological pattern describing the increase in the observed species richness with the length of time censused. Understanding STRs is important for understanding the ecological processes underlying temporal turnover and species richness. However, accurate characterization of the STR has been hampered by the influence of sampling. I analysed STRs for 521 breeding bird survey communities. I used a model of sampling effects to demonstrate that the increase in richness was not due exclusively to sampling. I estimated the time scale at which ecological processes became dominant over sampling effects using a two‐phase model combining a sampling phase and either a power function or logarithmic ecological phase. These two‐phase models performed significantly better than sampling alone and better than simple power and logarithmic functions. Most community dynamics were dominated by ecological processes over scales <5 years. This technique provides an example of a rigorous, quantitative approach to separating sampling from ecological processes.     

A Comparison of Remote Sensing and Ground-Based Methods for Monitoring Wetland Restoration Success

Abstract Efficient and accurate vegetation sampling techniques are essential for the assessment of wetland restoration success. Remotely acquired data, used extensively in many locations, have not been widely used to monitor restored wetlands. We compared three different vegetation sampling techniques to determine the accuracy associated with each method when used to determine species composition and cover in restored Pacific coast wetlands dominated by Salicornia virginica (perennial pickleweed). Two ground‐based techniques, using quadrat and line intercept sampling, and a remote sensing technique, using low altitude, high resolution, color and color infrared photographs, were applied to estimate cover in three small restoration sites. The remote technique provided an accurate and efficient means of sampling vegetation cover, but individual species could not be identified, precluding estimates of species density and distribution. Aerial photography was determined to be an effective tool for vegetation monitoring of simple (i.e., single‐species) habitat types or when species identities are not important (e.g., when vegetation is developing on a new restoration site). The efficiency associated with these vegetation sampling techniques was dependent on the scale of the assessment, with aerial photography more efficient than ground‐based sampling methods for assessing large areas. However, the inability of aerial photography to identify individual species, especially mixed‐species stands common in southern California salt marshes, limits its usefulness for monitoring restoration success. A combination of aerial photography and ground‐based methods may be the most effective means of monitoring the success of large wetland restoration projects.     

Population genetic structure of the butterfly Melitaea didyma (Nymphalidae) along a northern distribution range border

The population genetic structure of the butterfly Melitaea didyma was studied along the northern distribution range border in Central Germany by means of allozyme electrophoresis. Individuals were sampled from a total of 21 habitat patches from four regions, and two provinces. Sampling was designed to estimate local vs. regional differentiation. High levels of variability were found, H _e= 0.14–0.21. The mean expected sample heterozygosity from one region, Mosel, was significantly lower than from the Hammelburg region, H _e= 0.17 and 0.19, respectively. Two hierarchical levels of genetic differentiation were found. Within regions individuals sampled from different patches behaved as belonging to one population with high levels of gene flow (Hammelburg F _ST= 0.015, Mosel F _ST= 0.044), though local isolation barriers did create a substructuring of these populations. The inbreeding coefficients, F _IS, were constant over all sample levels, suggesting a similar distribution of habitat patches within regions. Between regions gene flow was limited. An isolation by distance analysis indicated that the hierarchical structure, at the provincial level, may be breaking down due to isolation of regional populations. A more general observation was that the sampling design may greatly have influenced the estimation of genetic differentiation. Depending on which samples were included, overall F _ST estimates ranged from 0.059–0.090.     

两阶抽样中比率型估计量的平均精度

本文给出了两阶抽样中总体均值的比率型估计量的平均精度,它当样本容量充分大时主项不劣于无偏估计量的平均精度．     

菜蚜二项式抽样设计及其精度分析

１９９０～１９９２年间对杭州市郊区青菜上桃蚜（Ｍｙｚｕｓｐｅｒｓｉｃａｅ）、萝卜蚜（Ｌｉｐａｐｈｉｓｅｒｙｓｉｍｉ）及其混合种群的田间近１００组调查数据,利用每样方（株）虫口不超过数阈值Ｔ（分别为０、１、５、１０、２０、３０、４０）头蚜虫的植株比例（ＰＴ）与种群密度（ｍ,头·株－１）的关系,通过拟合经验公式ｌｎ（ｍ）＝ａ＋ｂｌｎ［－ｌｎ（ＰＴ）］而设计的二项式抽样．通过对三者不同数阈值（Ｔ）的回归决定系数（ｒ２）、种群密度的回归估计方差（Ｖａｒ（ｍ））、抽样精度（以ｄ表示）和实际应用等的比较,结果表明当桃蚜种群处于较高密度即ｍ≥１０时,其理想的Ｔ值为３０;当萝卜蚜种群处于较高密度即ｍ≥５时,其理想的Ｔ值为１０;而它们的混合种群未得到其理想的Ｔ值．数阈值Ｔ为３０和１０可分别用于桃蚜和萝卜蚜的二项式抽样设计．而传统的二项式抽样即０～１抽样由于应用于小白菜上菜蚜的抽样设计时产生很大的误差,不宜采用．