This study improves the theoretical framework of fertility decision making by arguing that in addition to macro and individual factors, social norms have a very important influence on fertility intentions. Our findings suggest that reshaping social norms regarding fertility is essential to enhance fertility rates in China.China’s low fertility rates are a major concern across all sectors of society. Fertility is a major issue related to economy, society and family development. Based on social norms theory, this paper explores the influence of social norms on individuals’ fertility intentions from two perspectives: spatial proximity and social proximity. Using data from the China Family Panel Studies, we found that individual’s fertility intentions were influenced by social norms; both neighborhood social norms and group social norms had significant effects. The role of social norms in shaping individual fertility intentions varied by gender,  Changes in population development dynamics affect the prospects of China’s economic and social development. Since the founding of the country, China’s fertility rate has fluctuated greatly see . Along wScholars have richly explored the causes of low fertility levels in China, offering explanations in terms of modernization and its associates [e.g., economic development , rising Chinese fertility culture  could be summarized with “many children, many blessings.” This ensured the survival of Chinese civilization against the background of high mortality rates. This traditional fertility culture lasted for thousands of years and was engrained as a social norm among the Chinese, thereby influencing individual’s family planning. After the founding of the People’s Republic of China (PRC), this fertility culture remained. Except for a brief decline due to external factors such as China’s Great Famine, China’s TFR remained high (around 5 or 6) from 1949 to the 1970s. However, the improvement of medical conditions and living standards after the founding of the PRC led to a rapid decline in mortality. This high birth rate, coupled with lower mortality rates, caused the rapid growth of China’s population. To alleviate the contradiction among population development, environmental capacity, and socioeconomic development, China began to implement the One-Child Policy (OCP). However, traditional fertility norms are inertial and persistent, resulting in a small drop in fertility when the OCP was first decreed . SubsequBased on the aforementioned analysis, this paper explores the influence of social norms on individual fertility intentions from two perspectives: spatial proximity and social proximity. This allows us to deepen our understanding of the causes of low fertility rates in China. The contributions of this paper are threefold: first, this study improved the theoretical framework of fertility decision-making, as social norms are the bridge between micro-and macro-factors that affect fertility intentions. Second, most existing studies have focused on explaining fertility from an economic perspective , thus faThe demographic transition (DT) refers to the process of population change from high to low birth and death rates. This demographic transition was based on industrialization and modernization, and the development of economic and medical technology has led to a decline in mortality and an increase in infant survival . HoweverThe social drivers of SDT were not the same as those of demographic transition. SDT suggests that the driving mechanisms behind low fertility are structural social changes, cultural transmutations, and technological innovation. Among these, cultural transmutations are central driving forces. Cultural values occupy a central position in SDT and are intrinsic drivers of changes in marital behavior. SDT argues that the rise of individualism and feminism, gender equality in society, and changes in the concepts of marriage and family are important causes of low fertility intentions and low fertility in postmodern societies .Gender revolution is also essential for explaining generally low intentions to marry and fertility. In the first stage of the gender revolution, the increase in women’s education and labor force participation rates broke the previous social structure of the public and private spheres and the gendered division of labor. Women objectively took on more economic functions and subjectively no longer wanted to be confined to the role of the housewife. However, the entrenchment of established gender norms and institutions has led to more severe work—family conflicts for women, which, in turn, has reduced their intentions to marry and have children, leading to a steady decline in marriage and fertility rates .In the second phase of the gender revolution, women’s share of the labor market continues to rise, and gender equality in the public sphere is no longer the only gender revolutionary pursuit for women. Thus, a force for change in the family sphere has developed, and pressure has begun to mount on men to increase their home caring. Driven by a more egalitarian gender perspective, men enter the private sphere more actively and take on family responsibilities, thus contributing to a new equilibrium between stable marriages and rising fertility rates .However, there is more resistance to men entering the private sphere than women entering the public sphere. In many countries, the second part of the gender revolution still lags after women have entered the labor market . Women aSocial Norms are standards of behavior that are widely accepted by members of a group in a given situation . They alDuring the fertility transition, sociologists and demographers began to focus on the influence of social norms on fertility decisions. Since the 1980s, social interactions and perceptual factors have been used to explain the decline and spread of fertility in Europe . The rolLooking back at the history of China’s population development see , the TFRThe first is modernization. Based on DT, industrialization and modernization are believed to lead to a decline in fertility intentions . ImproveThe second is the fertility policy. In the early 1970s, the promotion of “late marriage and late childbearing” and “fewer and better births” guided individuals to change from having more children to having fewer. The TFR dropped from 5.81 in 1970 to 2.75 in 1979. In 1980, China formally implemented a family planning policy with the “One-Child Policy” as the main content. Under the combined effect of strict family planning policy and economic development, China’s TFR declined from approximately 2 to <1.5 in the 1990s. Since the 21st century, the fertility rate has been very low . China bThe third is the demographic transition. China has completed its first demographic transition, and fertility has remained below the replacement level for a long time. In addition to the influence of population policy and modernization processes, the SDT is also an important mechanism leading to China’s current low fertility rate. China is currently at the beginning of its SDT . SeveralWomen enjoy a higher social status and gender equality policies are well implemented in China, and the labor force participation rate of women is high. Simultaneously, Confucian culture profoundly influences China, and women take on traditional family service roles in their households. Therefore, Chinese women shoulder the dual responsibility of social work and family care and face a career-fertility dilemma, an essential factor that reduces women’s fertility intentions . The secThrough the review of the aforementioned literature, it could be discovered that the majority of these studies analyzed the influence of individual factors and macro-factors on fertility intention from the perspective of economy . HoweverGenerally, individuals’ fertility intentions are influenced by two major factors: macro-level modernization, fertility policies and micro-level individual factors . AdditioThe impact of modernization and fertility policies on the population is not only a change in demographic structure, population development, and population fertility status but also has a more critical connotation of changes in social norms about fertility. While social norms, as informal institutions, do not have as noticeable a constraining effect on individuals’ fertility behavior as formal institutions, relatively flexible social norms may have a more pervasive, deeper, and longer-lasting impact. In particular, social norms maintain inertia when the socioeconomic situation and fertility policies change and continuously influence individual fertility behaviors .The direct effects of macro factors on fertility intentions and the effects of individual characteristics on fertility intentions have been well discussed in the existing literature . HoweverAccording to social norms theory, individuals’ fertility decisions are influenced by the social norms of the reference group . Social China’s cultural context provides a unique case study for examining the relationship between social norms and fertility. First, China has a robust collectivist outlook, and social norms are more influential. Second, China has implemented family planning policies since 1980, which rapidly changed the fertility behavior of residents and shaped the social norm of “fewer and better births.” The fertility concept of “fewer children, better births, later marriage, and later childbearing” is spreading rapidly among the new generation of young people. Simultaneously, the implementation of family planning has led to a rapid increase in women’s educational level, status, and labor force participation rate . These fThird, significant differences in economic development, social customs, and cultural environments among the Chinese provinces have led to more pronounced regional sub-cultural differences. Therefore, there are also regional differences in fertility culture and attitudes shaped by macro factors . For exaIndividuals develop their fertility preferences by adhering to social norms, which are derived from reference groups in close proximity. These groups can be inherited from the family (family members and religion) and from living communities and workplaces (neighbors and coworkers) . Modern Spatial proximity refers to members living within the same community. Overly large geographic areas or too many people make it challenging to generate communication and cause difficulties in interactions among residents. Thus, an appropriate scope must be chosen to reflect the influence of social norms. Therefore, we propose the following hypotheses:Hypothesis 1: Neighborhood social norms based on spatial proximity have a significant effect on individuals’ fertility intentions.Social proximity refers to members of the same broad occupational group. The reason for using this reference group is that occupational identity is the most important social identity of an individual in social life. The occupational group is formed by different closed mechanisms  and has a high level of homogeneity. The nature of the occupation, the content of the work, and social interaction within the occupational group further reinforce occupationally compartmentalized attitudes, values, and lifestyles, which form shared social norms . DiffereTherefore, we propose the following hypotheses:Hypothesis 2: Group social norms based on social proximity have a significant effect on individuals’ fertility intentions.The data for this study were obtained from 2018 the China Family Panel Studies (CFPS), a national, large-scale, multidisciplinary, and comprehensive social tracking survey that examines changes in China’s society, economy, demographics, education, and health at the individual, household, and community levels. The CFPS adopts the implicit stratification method for multi-stage equal probability sampling; it covers 25 provinces/autonomous regions in China, which account for roughly 95% of the population. The main dependent variable in this paper is fertility intention, which is expressed by the answer to the questionnaire “How many children do you think is ideal for you to have?” The answer to this question for this question ranges from 0 to 10. Based on the distribution of the values of this variable, and to avoid the influence of extreme values, the values of “0” and “1” are combined into “1 or less,” whereas values of “3” or more are combined into “3 or more.”The core independent variable is the fertility social norms. For the measurement of this variable, it is first necessary to specify the reference group, which we define in terms of both spatial proximity and social proximity, according to the aforementioned hypotheses. For spatial proximity, the number of children in the community/ number of people of fertile age in the community  is calculated and categorized as the “neighborhood social norm.” For social proximity, the classification is based on the respondent’s occupation: farming, business owner, government/ institution/research institute/state enterprise, collective enterprise/ civil non-enterprise/association/community committee, private enterprise/individual business/foreign/Hong Kong, Macao, and Taiwan enterprises/other types of enterprises, and other occupations. The number of children of respondents in a given occupation/number of people of fertile age in a given occupation  is calculated separately as the group social norm. We use fertility behaviors as proxy for norms because individuals are more likely to observe the former and infer social norms from it. It is difficult for individuals to observe the fertility preferences of others, but it is easy to observe actual fertility behavior . At the hukou, marital status, ethnicity, health, and siblings were selected as control variables  less likely to have more children. The effect of age on fertility intention shows an inverted U-shape, i.e., the older the individuals is, the higher their fertility intentions; however, after a certain age, fertility intentions gradually decreases. Moreover, the higher the education, the lower the fertility intentions. Individuals with higher education have higher expectations of their career and income, and pay more attention to the realization of their values, and have a higher opportunity cost for having children, that means they are more inclined to have fewer and better children. Han Chinese have lower fertility intentions than other ethnic groups and are more likely to develop low fertility preferences under the long-term implementation of the OCP. Urban residents exhibit lower fertility intentions. The urban and rural areas differences in fertility policies, economic development, and childcare costs lead to the differences in fertility intentions. Additionally, the more siblings an individual has, the higher fertility intention, that comes from the influence of social norms within the family of origin. The increase in personal income eases the financial pressure to have children and boosts fertility confidence. Real estate, as a wealth effect, has a positive effect on fertility intentions.To verify the robustness of the results, we used substitution of core variables and redefinition of fertility intentions to perform robustness tests. First, Ologit, Oprobit, and ordinary least squares (OLS) models were used to analyze the effect of social norms on individuals’ fertility intentions, and the results are shown in Panel A of Under China’s urban–rural dual system, there are significant differences in fertility social norms between urban and rural residents due to differences in fertility policies and socioeconomic environment. Overall, China is a typical acquaintance society, and this characteristic is more prominent in rural areas, where residents are interconnected in a tight social network . Rural rTherefore, the samples were divided into urban and rural sub-samples to examine the urban–rural differences in the influence of social norms on fertility intentions. As shown in There are significant differences between men and women in the fertility decision-making process. On the one hand, the gender concept of “men dominate outside and women dominate inside” makes men more susceptible to social norms in traditional Chinese culture. Male social networks are more extensive than females, and men are more “face-conscious” in social activities and more interested in gaining the approval of others . As a reThe overall samples were further divided by gender to further explore the differences in the influence of social norms. As shown in Research has shown that, following significant life events such as marriage or childbirth, people tend to align with existing social norms to avoid cognitive dissonance, a phenomenon known as the adaptation effect . Those wThe most important life course change for fertility behavior is whether or not to marry. Therefore, we divided respondents’ life course stages according to marital status (unmarried vs. married) to further examine the influence of social norms. As shown in Low fertility levels are a major challenge for several countries, and China’s current low fertility rate is an issue of concern for all sectors of Chinese society. Low fertility problem not only affect countries’ population size and demographic structure, but also their future innovation and development capacity. Thus, it is important to clarify the causes of low fertility levels in China. The implementation of the OCP not only changed people’ fertility behavior but also had a profound impact on the traditional concepts and social norms related to fertility. However, the transformation of social norms is a gradual process, which is why the effects of OCP persist even years after China’s fertility policy has shifted.hukou, and life course; specifically, men, rural residents, and married individuals were more significantly influenced by social norms.We explored the influence of social norms on individuals’ fertility intentions from two perspectives: spatial proximity and social proximity. The study found that individual’s fertility intentions were influenced by social norms; both neighborhood social norms and group social norms had significant effects. The role of social norms in shaping individual fertility intentions varied by gender, There is a lack of research on the correlation between social norms and fertility intentions in the Chinese context. Our study verified that fertility intentions were significantly and positively associated with neighborhood social norms and group social norms. The fertility intention of individuals increased by 15.10% for every unit increase in the actual fertility rate of the community, and increased by 8.10% for every unit increase in the actual fertility rate of the occupation. We confirmed that social norms were an important factor affecting individuals’ fertility intentions and provided empirical support for the theoretical framework outlined in the preceding section. The analysis of the trends in fertility levels in China  revealedIn contrast, modernization and fertility policies may also moderate the role of social norms on individual fertility intentions. Modernization may weaken the influence of social norms on individuals. The improved status of women, rise of individualism, modernization of fertility, and increased sense of independence brought about by modernization may weaken the influence of social norms on fertility intentions. In the urban–rural heterogeneity test, we found that urban residents were less influenced by social norms than rural ones. The degree of modernization and urbanization was generally higher in urban regions than in the rural, and urban residents had more modern concepts and a stronger sense of independence, and therefore, they were less influenced by social norms . FertiliIn China’s urban–rural dual system, urban and rural residents have different fertility intentions and are influenced by different social norms. China has a large urban–rural migrant population, with many migrants from rural areas living in cities for many years. Immigrant integration theory suggests that migrants are influenced by the social norms of the place they move to and adjust their fertility intentions, eventually resulting in a convergence of fertility behaviors between immigrants and local residents . TherefoGender differences in fertility intentions suggest that women have lower fertility intentions and are less positively influenced by social norms, possibly due to the higher opportunity costs of childbearing and the possibility of facing motherhood punishment. The traditional division of gender roles in China makes the involvement of fathers in the child-rearing process less frequent or even nonexistent. The excessive pressure of childcare also reduces women’s fertility intentions . In the Our research on life-course differences shows that unmarried individuals are less influenced or even negatively influenced by group social norms. Unmarried individuals comprise the main group for future fertility, and timely changes their fertility perceptions could have an important impact on future fertility levels. It has been shown that social propaganda and national media has an important role in shaping individual perceptions and values . Many yoBased on social norms theory, this paper explored the influence of neighborhood social norms and group social norms on individual fertility intentions. By using 2018 CFPS data, we found that: (i) Individuals’ fertility intentions differ across regions and occupational groups, with the highest fertility intentions being found in the western region, followed by the central and eastern regions. Additionally, farmers and business owners exhibited higher fertility intentions, while those who worked in government/institutions/research institutes/state-owned enterprises exhibited the lowest fertility intentions. (ii) Individuals’ fertility intentions were positively influenced by neighborhood social norms and group social norms, i.e., the higher the actual fertility rate within their community and occupation, the higher the fertility intentions. (iii) Rural residents and men were more influenced by social norms, compared with urban residents and women, respectively. Individual fertility intentions were influenced by social norms differently depending on their life course.This paper improves the theoretical framework of fertility decisions by incorporating social norms factors into fertility decisions. The role of social norms in shaping individuals’ fertility intentions explains why no timely shift in fertility levels has occurred after the Chinese adjustment of its fertility policy. The persistence and inertia of the influence of low-fertility social norms on individuals’ fertility intentions should be recognized. Moreover, the influence of neighborhood social norms on fertility intention explains the regional differences in fertility levels in China, while group social norms explain the differences in fertility levels among people with different occupational backgrounds. Our study verified the role of social norms in shaping individuals’ fertility intentions. Therefore, in the process of raising fertility levels and reshaping social norms on fertility, it is important to give full play to the power of communities, groups. Publicity to encourage fertility is placed in the community and workplace to strengthen public opinion and policy guidance. At the same time, we note that compared with group social norms, neighborhood social norms play a greater role. Therefore, community can play a more effective role in creating the fertility-friendly environment society.The present study has several limitations. First, social norms influence individuals’ perceptions and behaviors, especially through the important individuals in social networks. However, because the survey data we used did not contain information on social networks and social interactions, we were unable to test the influence of important individuals on individuals’ fertility perceptions. Second, China implemented the Universal Two-Child policy in 2016. The fertility policy adjustment may lead to changes in fertility intentions. Our research data were cross-sectional and we were unable to completely strip the influence of social norms and the new policies on fertility intentions. Bridging these limitations will the focus of our future research.http://www.isss.pku.edu.cn/cfps/.Publicly available datasets were analyzed in this study. This data can be found at: The studies involving human participants were reviewed and approved by Member of Biomedical Ethics Committee of Peking University. The patients/participants provided their written informed consent to participate in this study.XY and JL contributed to conception and design of the study and wrote sections of the manuscript. JL performed the statistical analysis and wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.This research was funded by Major project of the Key Research Institute of Humanities and Social Sciences of the Ministry of Education in China (17JJDGJW006) and the National Social Science Fund of China (18BRK024).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In addition, an increased landing height (p = 0.010), not loading (p > 0.05), significantly impaired ankle inversion discrimination sensitivity. In conclusion, compared to non-CAI, individuals with CAI showed significantly worse ankle inversion proprioceptive performance during landing. An increased landing height, not loading, resulted in decreased ankle proprioceptive sensitivity. These findings suggest that landing from a higher platform may increase the uncertainty of judging ankle positions in space, which may increase the risk of ankle injury.Proprioception is essential for neuromuscular control in relation to sport injury and performance. The effect of landing heights and loads on ankle inversion proprioceptive performance in individuals with or without chronic ankle instability (CAI) may be important but are still unclear. Forty-three participants (21 CAI and 22 non-CAI) volunteered for this study. The Ankle Inversion Discrimination Apparatus for Landing (AIDAL), with one foot landing on a horizontal surface and the test foot landing on an angled surface , was utilized to assess ankle proprioception during landing. All participants performed the task from a landing height of 10 cm and 20 cm with 100% and 110% body weight loading. The four testing conditions were randomized. A repeated measures ANOVA was used for data analysis. The result showed that individuals with CAI performed significantly worse across the four testing conditions ( Ankle sprain is a common sports injury  that usuPrevious biomechanical studies ,15 suggeLoad is known to affect perceptual and motor system performance by altering postural control and proprioception. For instance, extra body weight can reduce postural-stability control and the sensory pathways from the foot sole ,21. HoweCAI is a condition characterized by pain, weakness, reduced ankle range of motion, perceived ankle “giving way” sensation, and proprioception deficit, which may lead to recurrent ankle sprains ,26,27,28Accordingly, the aim of this study was to test the ankle inversion proprioception of individuals with and without CAI when they landed at different heights with different loads. We hypothesized that an increased landing height may reduce ankle proprioception, but extra loads may reverse this, and individuals with CAI would perform significantly worse than those without CAI.A cross-sectional study was performed between June and July 2021 according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations.Forty-three participants were recruited (21 CAI and 22 non-CAI). To be eligible, the CAI participants must have had the following: (i) at least one ankle sprain that caused an inflammatory reaction  in the previous 12 months; (ii) at least two episodes of ankle instability “giving way” or repeated sprains within 6 months before the test; (iii) a Cumberland Ankle Instability Tool score (CAIT)  of <24; The study was conducted in accordance with the Declaration of Helsinki and was approved by the Shanghai University of Sport Ethics Committee (102772021RT073). Written informed consent was obtained from participants before data collection.This study utilized the AIDAL to measure the acuity of ankle inversion proprioception during landing . This meBefore the AIDAL’s data collection, each participant had three rounds of familiarization of the 4 possible ankle inversions in order , and they were required to remember the four different ankle inversions during the familiarization session. Participants then undertook 40 trials of testing, with 10 for each inversion position presented randomly. Participants were required to make an absolute judgment about the ankle inversion angle on each testing trial, and the numbers  with which the participant responded were collected, and without feedback being given as to the correctness of their judgements.The weight-adjustable vest c,d was uThe experiment was conducted in a university laboratory. All participants were tested with bare feet. For the non-CAI group, the testing foot was randomly selected, and for the CAI group, with unilateral CAI (n = 10), we tested the affected ankle, and with bilateral CAI (n = 11), we tested the ankle with a lower CAIT score. The flow chart of this study is shown below . All parp value of 0.05 or less was used to determine statistical significance. A total of 40 presentations of ankle inversion and related participant responses were inputted into SPSS to generate a receiver operating curve (ROC), and the area under the curve (AUC) was calculated as the ankle proprioception discrimination sensitivity. The AUC value ranges between 0.5 and 1. A higher value represents more accurate proprioception sensitivity.SPSS version 25  was used for data analysis and a Given that the data for the two groups were normally distributed, to determine the effect of CAI, landing heights and loads on ankle proprioception, a repeated measures ANOVA was conducted on the AUC scores.p = 0.018, partial η2 = 0.130) and the ankle proprioception AUC scores of 20 cm landing height were significantly lower than that of 10 cm landing height   or an interaction effect of height, load, and presence of CAI (Demographic information of the included participants is reported in = 0.150) . Howevere of CAI .Consistent with our hypothesis, we found that the overall ankle inversion proprioceptive performance of CAI patients was significantly worse than that of non-CAI participants, suggesting that CAI patients have impaired proprioceptive control when landing on an uneven surface. In addition, ankle proprioceptive discrimination sensitivity was significantly worsened by an increased landing height, but not loading , which wOur results showed that the proprioceptive acuity of CAI participants was significantly worse than those without CAI across the four different testing conditions. These findings are consistent with prior studies ,41 and fIn terms of the effect of landing height on lower limb biomechanics, research has shown that with increasing landing height, the ankle dorsiflexion, knee extension, and peak ankle plantarflexion moments are significantly altered in individuals with CAI . The resHowever, we found an extra 10% of body weight for the proprioceptive measurement did not differ from 100% body weight conditions. This evidence is contrary to the argument that ankle proprioception simply relied on mechanoreceptors around the foot–ankle complex . Han et This study compared ankle inversion proprioception during landing in both CAI and non-CAI populations in the face of height and loading conditions. One of the limitations of this study was that we did not collect data about the physical activity and occupation of the participants included in this study, which may have an impact on the results. Furthermore, we did not quantify kinematic patterns so that precise changes in movement extent of the participants at different heights and loading states to be observed. We did not use any instruments to control whether participants had a balanced distribution of weight between the two feet, a feature which should be improved for future study. In addition, previous research has shown that female and male individuals with CAI performed differently on a range of functional tasks . HoweverCompared to non-CAI, individuals with CAI showed significantly worse ankle inversion proprioceptive performance during landing. An increased landing height, but not loading, resulted in decreased ankle proprioceptive sensitivity. These findings suggest that landing from a higher place may increase the uncertainty of judging ankle positions in space, and thus increases the risk of ankle injuries. Therefore, jump-landing exercise from different heights may be important for ankle injury prevention and rehabilitation. Future research may investigate the effects of a rehabilitation program targeting ankle inversion proprioception during landing and explore the peripheral and central mechanisms associated with these effects.


Turing-Church computations are not interactive, and interactive machines can accomplish things that no Turing-Church computation can accomplish. Hence, if “rationality” is computation, and “bounded rationality” is computation with limited complexity, then “embodied bounded rationality” is both more limited than computation and more powerful. By embracing interaction, embodied bounded rationality can accomplish things that Turing-Church computation alone cannot. Deep neural networks, which have led to a revolution in artificial intelligence, are both interactive and not fundamentally algorithmic. Hence, their ability to mimic some cognitive capabilities far better than prior algorithmic techniques based on symbol manipulation provides empirical evidence for the principle of embodied bounded rationality.“Rationality” in Simon's “bounded rationality” is the principle that humans make decisions on the basis of step-by-step  reasoning using systematic rules of logic to maximize utility. “Bounded rationality” is the observation that the ability of a human brain to handle algorithmic complexity and large quantities of data is limited. Bounded rationality, in other words, treats a decision maker as a machine carrying out computations with limited resources. Under the principle of embodied cognition, a cognitive mind is an  From a computer science perspective, a rational process is step-by-step reasoning using clearly explicable rules of logic. Intractability arises when the number of steps or the amount of data that has to be stored gets too large. Simon's bounded rationality Simon,  can be iComputers, on the other hand, are superbly matched to this sort of rational process. When a decision problem can be formulated as an optimization problem with a clearly defined cost function, an algorithm can often be devised to make an optimal decision. These algorithms are rational in the same sense; they are step-by-step procedures where each step is justified using explicable rules of logic. Such algorithms have repeatedly proven tractable to computers even when hopelessly intractable to humans. When they prove intractable to computers as well, we can often refine them with heuristics and approximations that lead to close to optimal solutions, but even these heuristics are explicable and hence rational.Among the successes of such computer-driven decision-making are those that lie in the field of optimal control, where a machine makes decisions in response to sensor inputs, and these decisions are used to drive actuators that change the physical world in such a way as to feed back into the sensors. Self-driving cars, industrial robots, automated trains, and the electric power grid are all examples of such systems. The algorithmic decision-making in these systems interacts with the physical world in such a tight feedback loop that the behavior of the computer cannot be decoupled from the behavior of its physical environment. A whole branch of engineering called “cyber-physical systems” (CPS) has arisen to address the technological problems around such embodied robots Lee, .Today, to the surprise and, in some cases, extreme frustration of many researchers, many optimization solutions in engineering are being routinely outperformed by deep neural networks (DNNs). While DNNs are often described as “algorithms,” they do not rise to the level of “rational decision making” in the same sense. Although DNNs are typically realized algorithmically on computers, when a DNN produces a result, e.g., classifying an image as a Stop sign, there is no sequence of logical steps that you can point to that rationally leads to the classification. The classification is more like intuition than rationality.The AlphaGo project  do not have the capability to make the kinds of rational decisions that economists assumed they would. In his words:Theories that incorporate constraints on the information-processing capacities of the actor may be called theories of bounded rationality Simon, .He identified three limitations: uncertainty about the consequences that would follow from alternative decisions, incomplete information about the set of alternatives, and complexity preventing the necessary computations from being carried out. He argued that “these three categories tend to merge,” using the game of chess as an example and saying that the first and second, like the third, are fundamentally an inability to carry out computation with more than very limited complexity:What we refer to as “uncertainty” in chess or theorem proving, therefore, is uncertainty introduced into a perfectly certain environment by inability—computational inability—to ascertain the structure of that environment Simon, .Three decades later, he reaffirmed this focus on the process of reasoning:When rationality is associated with reasoning processes, and not just with its products, limits on the abilities of Homo sapiens to reason cannot be ignored Simon, .Reasoning and rationality as computation are central to his theory, and he argued that economists' assumptions that agents would maximize expected utility was unrealistic in part because that maximization is intractable to a human mind.The Master Algorithm, states that Newton's second law is an algorithm. Often expressed as F = ma, force equals mass times acceleration, Newton's second law is not an algorithm. There are no steps, there is no procedure, and there is no end. Instead, Newton's second law is a relation between two continuously varying quantities, force and acceleration, where the latter quantity expresses a rate of change of velocity, which in turn expresses a rate of change of position. Domingos seems to use the word “algorithm” to mean anything that is formally expressible. In this article, I will use the term “algorithm” in a narrower manner consistent with the Merriam-Webster definition.What is an algorithm? Merriam-Webster gives this definition: “a step-by-step procedure for solving a problem or accomplishing some end.” Despite the simplicity of this definition, the term is widely used more broadly. Domingos , for exathere is no algorithm. Every algorithm that attempts to simulate a process described by such a differential equation is flawed. Newton's second law is a linear differential equation for which, for many input force functions, we can find a closed-form solution. Once we have such a solution, we can devise an algorithm that gives the position at any chosen point in time. However, for non-trivial force inputs, and for most non-linear differential equations, there is no such closed-form solution, and every algorithmic approximation exhibits arbitrarily large errors. Non-linear differential equations, in particular, often exhibit chaotic behavior, where arbitrarily small errors at any step become arbitrarily large errors in future steps. The discovery of such chaotic behavior is attributed to Lorenz  and a slow style (System 2). The slow style is capable of algorithmic reasoning, but the fast style, which is more intuitive, is responsible for many of the decisions humans make. It turns out that many of today's artificial intelligences (AIs) more closely resemble System 1 than System 2. Even though they are realized on computers, they do not reach decisions by algorithmic reasoning.Kahneman, in his book, “Computation,” in the sense that I am using the term in this article, is not the same as information processing, in the sense used in Dodig-Crnkovic and Giovagnoli , Müller In Lee  (Chaptermay be finite or countably infinite” (emphasis added), and then implying that it is always finite or countably infinite. Goyal  is a matter of faith, not science.Given these facts, we are forced to make one of two choices: either (A) information processing is richer than computation, or (B) the physical world does not have uncountable alternatives, Hypothesis (B) is sometimes called “digital physics”  can only be defended by a circular argument.If anything in the physical world forms a continuum , then noise in measurements remains possible, no matter how good the measurement apparatus becomes. This follows from the incompleteness of determinism Lee, . A noiseHypothesis (B) is not only a matter of faith, but it also a poor choice under the principle of Occam's razor. As I point out in Lee  Chapter who statDeep neural nets (DNNs), which have transformed technology by enabling image classification, speech recognition, and machine translation, to name a few examples, are inspired by the tangle of billions of neurons in the brain and rely on the aggregate effect of large numbers of simple operations. They are, today, mostly realized by computers, and hence are composed of “algorithms” and “computation.” However, to view these realizations as Turing-Church computations is to ignore the role of feedback, a property absent in the Turing-Church model. This role is not incidental. Moreover, it also ignores the possibility that today's realizations of neural networks are brute force computational approximations of information processing that is not, at its root, computational.any decision. This could start with a generative-adversarial network (GAN) that learns to provide explanations that appear to be generated by humans.A frustrating result of the recent successes in deep neural nets is that people have been unable to provide explanations for many of the decisions that these systems make Lee, . In factpost hoc rationalizations, offering as explanations factors that do not or cannot account for the decisions we make. This fact about humans is well-explained by Kahneman, whose work on “prospect theory,” like Simon's bounded rationality, challenged utility theory. In prospect theory, decisions are driven more by gains and losses rather than the value of the outcome. Humans, in other words, will make irrational decisions that deliver less value to them in the end. In Thinking Fast and Slow, Kahneman offers a wealth of evidence that our decisions are biased by all sorts of factors that have nothing to do with rationality and do not appear in any explanation of the decision.Humans are very good at providing explanations for our decisions. But our explanations are often wrong or at least incomplete. They are likely to be Kahneman reports, for example, a study of the decisions of parole judges in Israel by Danziger et al. . The stuThe authors carefully checked many alternative explanations. The best possible account of the data provides bad news: tired and hungry judges tend to fall back on the easier default position of denying requests for parole. Both fatigue and hunger probably play a role  encodes knowledge as production rules, if-then-else statements representing the logical steps in algorithmic reasoning  to what really was excessive hyperbole about AI at the time. They were just the tip of a broad backlash against AI that came to be called the “AI winter,” where funding for research and commercial AI vanished nearly overnight and did not recover until around 2010.DNNs work primarily from examples, “training data,” rather than rules. The explosion of data that became available as everything went online catalyzed the resurgence of statistical and optimization techniques that had been originally developed in the 1960s through 1980s but lay dormant through the AI winter before exploding onto the scene around 2010.specifies a taxonomy rather than recognizing an objectively existing one. Because training images are labeled by humans, the resulting taxonomy is familiar to humans.DNNs particularly excel at functions that, in humans, we call perception, for example the ability to classify objects in an image. Stewart  attributThe techniques behind the AI renaissance are nothing like the production rules of GOFAI. A central one of these techniques, now called backpropagation, first showed up in automatic control problems quite some time ago. Kelley  describeBased in part on Kelley's work, Bryson et al.  describeBackpropagation can be thought of as a technique for a system to continuously redesign itself by probing its environment (including its own embodiment) and adapting itself based on the reaction. DNNs realized in software are better thought of as programs that continuously rewrite themselves during their training phase. Today, it is common to freeze the program after the training phase, or to update it only rarely, but this practice is not likely to persist for many applications. Continuing to learn proves quite valuable.algorithmic reasoning, where the result of the training phase is a set of explicable production rules, but these have proven to underperform neural networks. Wilson et al. , those symbols have no relationship to the problem they are solving.is an interaction of a brain with its body and environment. A cognitive being is not an observer, but rather a collection of feedback loops that include the body and its environment. Fundamentally, under this thesis, a cognitive mind is an interactive system.In the thesis of embodied cognition, the mind “simply does not exist as something decoupled from the body and the environment in which it resides” Thelen, . The minIf “rationality” is computation, and “bounded rationality” is computation with limited resources, then “embodied bounded rationality” is both more limited than computation and more powerful. By embracing interaction, embodied bounded rationality can accomplish things that bounded rationality or even unbounded rationality alone cannot.Turing-Church computation is not interactive. There is no part of the theory that includes effects that outputs from the computation may have on inputs to the computation. Central to what a computation is, in this theory, is that the inputs are fully available at the start, and that the outputs are available when the computation terminates. If the computation does not terminate, there is no output and the process is not a computation. There is nothing in the formalism that enables the machine to produce intermediate outputs, allow the environment to react and provide new inputs, and then continue by reacting to those new inputs. The “universal” Turing machine proves to be far from universal because it does not include any such interactive machines.To understand this point, it is critical to realize that the behavior that emerges from an interactive machine is not just a consequence of what the machine does, but also of what the machine's environment does. Hence, the only way to make Turing-Church computations truly “universal,” including interactive machines, is to ensure that their environment is part of the Turing-Church computation. To do this in general, you have to assume digital physics, something you can only do on faith.The biggest breakthroughs in AI replace the prior open-loop good old-fashioned AI (GOFAI) techniques with interaction and feedback. Here, I use the term “feedback” for interaction where one part of the system provides a stimulus to another part, measures its response, and adjusts its actions to make future responses more closely resemble its goals. Deep neural networks are, fundamentally, feedback systems in this sense, and they yield results of such complexity as to be inexplicable  and its environment (the roadway). This solution is extremely simple, a feedback control system realizable with technology that was patented back in the 1930s .Brooks' vision was perhaps first demonstrated in real robots by Bongard et al. . Their rPfeifer and Bongard  assert tThe classical servo-based robot control systems are simple feedback control loops like those developed by Black . With a I Am a Strange Loop, Hofstadter states:Higher-order cognitive feedback loops also enable humans to recognize flaws in our plans and attempt to improve them. Supporting Clark's argument, in You make decisions, take actions, affect the world, receive feedback, incorporate it into your self, then the updated “you” makes more decisions, and so forth, round and round  to some measure of health. Suppose that there is risk of some factor that causes a patient to be more or less likely to take the treatment and also affects the patient's health. Such a factor is called a “confounder” in statistics. The confounder could be, for example, gender, age, or genetics. To be specific, suppose that the treatment for some disease is more appealing to women than men, and that women tend to recover more from the disease than men. In that case, gender is a confounder and failing to control for it will invalidate the results of a trial.In many cases, however, we don't know what confounders might be lurking in the shadows, and there may be confounders that we cannot measure. There might be some unknown genetic effect, for example. We can't control for confounders that we can't measure or that we don't know exist. Is it hopeless, then, to evaluate whether a treatment is effective?To guard against the risk of hidden confounders, Pearl and Mackenzie  point ouRandomized controlled trials (RCTs), are the gold standard for determining causation in medical treatments and many other problems. The way an RCT works is that a pool of patients is selected, and within that pool, a randomly chosen subset is given the drug and the rest are given an identical looking placebo. Ideally, both the patients and the medical personnel are unaware of who is getting the real drug, and the choice is truly random, unaffected in any way by any characteristic of the patients. The system is now interactive because we have forced the value of one of the variables, whether the drug is taken, for each of the patients, and then we observe the results.RCTs are actually routinely used in software today. It is common at Facebook, for example, when considering a change to the user interface, to randomly select users to whom a variant of the user interface is presented. The reactions of the users, whether they click on an ad, for example, can be measured and compared to a control group, which sees the old user interface. In this way, Facebook software can determine whether some feature of a user interface causes more clicks on ads. This process can be automated, enabling the software to experiment and learn what causes users to click on ads. This is a much more powerful form of reasoning than mere correlation, and it can result in software designing and refining its own user interfaces. The software can even learn to customize the interface for individual users or groups of users. This software is not realizing a Turing-Church computation because it is interactive. The users are an intrinsic part of the system.It is not always possible or ethical to conduct an RCT. Pearl and Mackenzie  documentprocess information from the environment, but there are also limitations in our ability to sense, to gather information from the environment.Two of the three limitations in human rationality identified by Simon , uncertasense-to-act connections, which even bacteria have, but also act-to-sense. To have cognitive function, you have to affect the physical world and sense the changes. Sense-to-act is open loop; you sense, you react. Combine this with act-to-sense, and you close the loop, creating a feedback system.Goddfrey-Smith  tells usvia a sense-to-act, act-to-sense feedback loop.Goddfrey-Smith  gives a Turing-Church computations can only sense-to-act. The formalism does not include any mechanism by which the computation can affect its own inputs.Sense-to-act and act-to-sense feedback loops are present in many higher level cognitive functions. Since at least the 1800s, psychologists have studied the phenomenon that the brain can internally synthesize stimulus that would result from sensing some action commanded by the brain. This internal feedback signal is called an “efference copy.” In speech production, for example, while the body is producing sounds that the ears are picking up, at the same time, the brain generates an efference copy, according to this theory, which is fed back into a different part of the brain that calculates what the ears should be hearing, an “expected reafference.” The brain then compensates, adjusting the motor efference to make the speech sound more closely resemble the expectation.Many psychologists today believe that efference copies help distinguish self-induced from not self-induced sensory stimulus. All animals with sensors have evolved some form of efference copy mechanism because otherwise they would react to their own actions as if those actions were imposed by their environment.The importance of the efference copy has been understood at some level since the nineteenth century. Grüsser  gives a Central to this thesis is that our knowledge of the world around us is not solely determined by stimulus that happens to arrive at our sensory organs, but rather is strongly affected by our actions. Without these feedback loops, we would not only suffer limited ability to perform the information processing on our inputs, but we would also have fewer and less meaningful inputs. Turing-Church computations have no efference copies and hence no mechanisms for gathering these more meaningful inputs.Lest the reader assume that act-to-sense only makes sensing more efficient, I will now give two rather technical demonstrations that act-to-sense enables making distinctions that are not discernible without feedback. The first of these is the Brock-Ackerman anomaly, a well-known illustration in computer science that observation alone cannot tell the difference between two significantly different systems.Consider the system shown Brock and Ackerman  then gavThe first realization produces outputs as it receives inputs. That is, as soon as it sees a 1 on its input, it will produce 1 on its output.The second realization waits until there are two inputs available before producing any output. That is, it will not produce any output until both 1 and 2 are available, at which point it will produce the sequence .To an outside observer that can only passively watch the behavior of this system, these two realizations are indistinguishable. The possible output sequences are exactly the same for the same input sequences. For example, if the system is presented with inputs (5) and (6), i.e., two sequences of length one, the possible outputs for either realization are , , , and . The choice of realization has no effect on these possibilities.Nevertheless, the two realizations yield different behaviors in some circumstances. Consider the system in With this example, Brock and Ackerman  proved twould be a Turing-Church computation). Only through interaction with the system is it possible to tell the difference. That argument depends on another celebrated result in computer science, Milner's concept of bisimulation.Note that the Brock-Ackerman system is not a Turing-Church computation because of the non-deterministic Merge subsystem. The Turing-Church theory admits no such non-determinism. In Chapter 12 of Lee , I show A “simulates” another B if, given the same inputs, A can match the outputs that B produces. Park  reasoning using systematic rules of logic to maximize utility. It becomes natural to equate rationality with Turing-Church computation. However, Turing-Church computation provides no mechanism for I have given a series of illustrations that show that interaction enables capabilities that are inaccessible to Turing-Church computation, including controlling a system in an uncertain environment, reasoning about causation, solving some undecidable problems, and discerning distinctions between certain kinds of systems. Bounded rationality, therefore, is not the same as a limited capacity to carry out Turing-Church computations because rational processes with feedback are capable of things that Turing-Church computations are not.is an interaction of a brain with its body and environment. So, while it is true that the human brain has limited Turing-Church computational capability, it also transcends such computation by interacting with its body and environment. Key features of cognition, such as the ability to distinguish self from non-self and the ability to reason about causation, depend on such interaction. Since such interaction is missing from the Turing-Church theory of computation, the “universality” of such computation falls far short of true universality.Interaction is the core idea in embodied cognition, which posits that a cognitive mind Deep neural networks, which have led to a revolution in artificial intelligence, are both interactive and not fundamentally algorithmic. Their ability to mimic some cognitive capabilities far better than prior algorithmic techniques based on symbol manipulation (“good old-fashioned AI”) provides empirical evidence for the power of embodied bounded rationality.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


As the most fundamental communication unit in the brain network, synapses are one of the hot topics in the field. In the past decade, numerous efforts have been invested into understanding the signaling mechanisms of synapse assembly, resulting in fruitful literature illuminating our understanding of synapse biology. This Research Topic aims to collect a series of studies on synapse formation research, especially inhibitory synapses.Imam et al. found a TC10-driven signaling mechanism in regulating the spatial organization of presynaptic neurotransmitter release at inhibitory synapses. Collybistin recruits gephyrin at inhibitory GABAergic synapses and interacts with small GTPases Cdc42 and TC10. The authors applied newly developed collybistin FRET sensors and investigated the molecular basis of the regulation of collybistin. Surprisingly, TC10 binds to closed/inactive collybistin, causing a switch from an auto-inhibited close state to an open/active state. This study suggests a new substrate in inhibitory synapse regulation.In a research article, Boxer and Aoto summarized the role of neurexins (Nrxns) and their ligands at inhibitory synapses in a review. Neurexins are evolutionarily conserved presynaptic cell adhesion molecules, and they are encoded by three genes, Nrxn1-3. Functional studies of Nrxns have focused mainly on glutamatergic synapses. However, the role of neurexins' molecular functions at GABAergic synapses has been elucidated in recent studies. Neurexins express in brain-region, cell-type, and synapse-specific manner, therefore, they also exhibit brain-region, cell-type, and synapse-specific dependent functions. Meanwhile, neurexin expression at inhibitory synapses is regulated by activity. Lastly, Boxer and Aoto summarized the binding partners of neurexins at inhibitory synapses, including neuroligins, cerebellins, dystroglycan, neurexophilins, calsyntenin-3, carbonic anhydrase-related proteins 10 and 11 (CA10/11), FAM19A1-4, GABAAR, and immunoglobulin superfamily member 21 (IgSF21).Moreover, Zhang et al. further summarized the progress of the signaling mechanism of voltage-gated calcium channels (CaV) at presynaptic active zones. Voltage-gated calcium channels at the presynaptic active zone are heterogeneously organized and highly diversified. CaV regulates the synapse functions not only by diverse CaV channel types but also by the expression of channel numbers. However, the organization is not chaotic or random. The spatial relationship between CaV channel clusters and synaptic vesicles is topographic and logical and can be modulated by G-protein coupled receptors.In another mini-review, Tang et al. discussed the synapse and synapse formation alterations under pathological conditions—sepsis-associated encephalopathy (SAE). Pathophysiological changes of SAE, including neuroinflammation, glial activation, and blood-brain barrier (BBB) breakdown, affect synapse formation and functions intensively. SAE inhibits synaptic plasticity, disrupts neurotransmitter balance, and damages myelin. Under SAE, synapse formation is largely affected due to the alternations of synaptic adhesion molecules, including neurexins and their ligands, and receptor protein tyrosine phosphatases. Synaptic modulation proteins, such as SYP, PSD95, and thrombospondin-1 (TSP1), also play vital roles during the process.Lastly, after a series of summaries and research on synapse signaling mechanisms under normal non-pathological conditions, In summary, the articles on our Research Topic provide a broad view and perspective of the signaling pathway of synapse assembly under normal and pathological conditions. Extensive progress has been achieved in this field recently. Therefore, it is of great importance to organize and summarize the discoveries and findings. Even though a huge amount of work has been done and many candidate genes and signaling pathways have been uncovered, this is only the tip of the iceberg. Numerous unanswered questions remain to be addressed in order to understand the signaling mechanisms during synapse formation fully.ZL drafted the editorial. RS, BZ, and XY edited and provided inputs. All authors contributed to the article and approved the submitted version.


In the non-growing season, beavers fell woody plants that they primarily use as a food source. It is well known that parameters such as woody plant availability, trunk diameter, and distance of woody plants from water influence food selection. Less information is available on the felling of specific species in different stand types where different forest management takes place. This makes the beaver a conflict species that causes damage to commercial forests, and information on foraging behavior in relation to environmental factors is very important. Especially as beaver populations continue to increase. In the three types of forest stands , species selection, the intensity of felling, the distance of felled woody plants, and trunk diameter vary. The beaver, which generally prefers non-commercial tree species , also adapts to and uses commercial oaks in commercial forests. These are most preferred at stand ages up to twenty years, i.e., smaller diameters but greater stand densities. The results suggest that by using knowledge of foraging behavior, economically profitable species can be protected by encouraging the non-commercial species most preferred by beaver (predominantly willow) near the shoreline. In addition, the natural tree composition around rivers or lakes will be promoted.Castor fiber Linnaeus, 1758). This study summarizes knowledge on non-vegetation diet selection by beavers in commercial and natural forests in the Czech Republic. A sample size of 25,723 woody plant specimens checked in 288 forest stands showed that beavers prefer willow, poplar, or hazel, but where these are less available, commercial tree species such as oak may dominate the diet and cause economic losses in forestry. Significant differences were also observed in a preference for different trunk diameters and distances from water in different types of stands. In terms of stand types, commercial monocultures are the most felled, while the probability of felling decreases with the age of stands. Based on these results and discussion, it is suggested that commercial forest stands including economically valuable woody plant species  could be protected through appropriate management measures, such as increasing the proportion of deciduous softwood stands along the riverbanks, which would distract the beavers from commercial woody plant species.Native ecosystems have been transformed by humans into cultural landscapes, resulting in the disruption of natural interactions, with some species unable to adapt and disappearing from such landscapes. Other species were able to adapt their behavior to current environmental conditions. In some places, forest management has gradually transformed native diversified forests into stands converted for the greatest profit in the wood matter, thereby affecting the food availability for herbivores, among them the Eurasian beaver ( Castor fiber Lin-naeus, 1758) was finally exterminated across much of their range in Europe in the 18th to 19th centuries [Aside from a few small reservoir populations, the Eurasian beaver  beavers utilize an opportunistic foraging strategy [Betula L. spp.) [Alnus L. spp.) [Salix L. spp.) and poplar (Populus L. spp.) [Both Eurasian and North American  ,20 or alL. spp.) , while aL. spp.) ,22,23. BL. spp.) . The samL. spp.) ,26,27.However, most studies focus on a summary evaluation of one type of landscape or forests without forest management. At the same time, beaver behavior can vary significantly in different types of forest stands. Of particular importance as regards economic losses caused by beavers ,28, it iQuercus L. spp.) and ash (Fraxinus L. spp.) [In the Czech Republic, beavers most frequently colonize floodplain forests along lowland rivers . Such foL. spp.) , the nat(a)Quercus and Fraxinus;To analyze on the individual woody plant level if there are preferences for some taxa of woody plants, especially for commercial species, i.e., (b)To analyze on the individual level, what is the role of distance from water and diameter of the woody plant on the probability of the felling by beaver and if these effects are taxa-specific;(c)To analyze on the patch level if some patch characteristics, primarily the type of forest stand , affect the proportion of felled basal area, the proportion of used woody plant taxa from their diversity in the stand, and the maximal distance of felled woody plants.The goals of the paper, therefore, are:Fraxinus excelsior L.), oak, elm (Ulmus L. spp.), and/or maple (Acer L. spp.) At the southern locality, the proportion of natural/near-natural growth is relatively low, while commercial species (dominated by oak) are grown in large monocultures of 1 to 2 ha. Woody vegetation tends to be dominated by oak, with a relatively high proportion of narrow-leaved ash (Fraxinus angustifolia Vahl.) and field maple (Acer campestre L.)Data were collected from two localities on the River Morava in the Czech Republic, one denoted as River Morava north  and the other River Morava south . Both localities are covered with lowland alluvial forests, a substantial part of which consists of commercial stands. At the northern locality, natural and close-to-natural stands predominate, with oak and ash grown commercially in small monocultures of up to 0.5 ha. Generally speaking, the dominant woody plant species in non-commercial plots are European ash  were staked out (short side to water). Each patch was then subdivided into four 5 × 5 m quadrats . If a be2)) was used to evaluate any differences in the proportion of felled woody plants, calculated using the formula: d = trunk diameter.The relative proportion of felled woody plants , the density of commercial woody plants, the diversity of woody plant taxa, the proportion of commercial woody plants from all woody plants, approximal age of the patch, and especially type of the patch . The proportion of felled basal area was analyzed by GLMM with beta distribution and logistic link from the library “glmmTMB” [Then we focused on the patch level and asked, which patch characteristics determine the overall proportion of felled basal area, the proportion of used woody plant taxa from their diversity in the patch, and the maximal distance of felled woody plant in the patch. As potential explanatory variables, we used the overall density of woody plants  recorded in the northern and southern locations of floodplain forests were determined. In terms of the basal area, oak and ash dominated with 37.63% and 13.63%, respectively, followed by willow with 9.33% and poplar with 9.14% . Using sdf = 20,561, χ2 = 1163.79, p < 0.001, Quercus, one of the most frequently felled and simultaneously commercial woody plants used as control, Alnus, Betula, Corylus, and Salix were not significantly different from Quercus and thus also frequently felled in the diet. Populus was even significantly more frequently felled than Quercus. Acer, Carpinus, and Ulmus belong to the group of genera significantly less frequently felled than Quercus, but still more often eaten than the rest of the woody plant genera  and differed among type of forest patches , but the mixed type differed .Working on the level of patches, the proportion of felled basal area decreased with the age of the patch  and natural  having similar proportion of consumed diversity as commercial ones.The proportion of woody plant taxa that showed herbivory from the patch diversity can be best explained by age of the patch and the density of woody plants. With increasing age of woody plants, this proportion decreased  and non-significantly shorter maximal distances in natural forests  than in the monoculture forest stands.The maximal distance of beaver felling can be best explained by age of the patch and the density of commercial woody plants. With increasing age of woody plants, this maximum distance decreased , relatively low biomass, and low density in some stands, trees with smaller diameters were sometimes “avoided”, probably due to the greater energy expenditure required to obtain them in such stands, and larger diameters were preferred, as in the case of oak or hazel. In addition, woody plant shoots that have been repeatedly felled may contain relatively high amounts of toxic secondary substances ,49,50. FPrevious studies on the winter diet of beavers in the Czech Republic have provided similar results concerning the preference for plants with a smaller diameter. Authors  noted thBeavers usually prefer the closest woody plants to the water. Most of the differences in each case could be attributed to local differences in the woody plants’ distribution from water. Using an aggregate sample, we were able to demonstrate that the probability of a woody plant being felled decreased with distance from water, with only exceptional cases far from a river attributable to the range of woody species on offer and the age structure of the stand. Overall, beavers appeared to concentrate their activity over a strip 1–10 m from the bank , though woody species were felled closest to the bank in natural/close-to-nature stands. The distance of felling was most likely affected by the distribution of woody plant species, the amount of woody plant biomass potentially usable by beavers, and available species composition. Natural forest stands are not managed, maintained, or harvested, thanks to which willow woody plants naturally occur close to the water (24%), allowing beavers to fulfill their dietary requirements without covering great distances. Previous studies also show that, in general, woody plants are felled near water, and with increasing distance from water, felling decreases, though the range of distances tends to vary at different sites. Some authors , for exaOverall, forest stand species composition is generally considered the main factor affecting beaver feeding behavior at most sites studied. Beavers are choosy generalists , who tenBeavers can cause considerable economic losses by felling woody plants in commercial forests . HoweverForest management has a significant effect on the selection of woody plants in the non-vegetation period. In natural forests, the selection of woody plants by beaver does not change significantly and is comparable to many previous results. However, the natural composition of woody plants was regulated around the rivers in the form of commercial stands with several species of commercial woody plants up to monocultures, where beavers showed a distinct preference for the most available woody plant species, in this case, commercial species such as oaks, leading to economic losses. With different types of management, not only the species selection changes but also the trunk diameter and the distance of felled woody plants from the water, which again affects the amount of damage. To combat this financial loss, we suggest that semi-natural buffer zones of softwood species along watercourses would reduce commercial losses, increase local biodiversity, and restore natural floodplain forests.


Bacterial species from the Weisella genus were predominantly present in FSm, NPm, and SDm, while Lactococcus dominated the MZm silage during early ensiling. Lactobacillus was predominant in all inoculated terminal silages. Overall, the four inoculated microbiota decreased the pH value of silage and were dominated by lactic acid bacteria (LAB); however, the NPm and SDm treatments resulted in comparatively higher AA contents which could have an inhibitory effect on the secondary fermentation developed by the yeast and enhanced the aerobic stability of forage sorghum silage.In this study, the effects of epiphytic microbiota from different forages on the fermentation characteristics and microbial community structure of forage sorghum silage were investigated. The gamma irradiated sterilized forage sorghum was treated through sterile water, epiphytic microbiota of forage sorghum (FSm), Sudan grass (SDm), Napier grass (NPm), and maize (MZm). NPm and SDm inoculated silages showed similar pH value and lactic acid (LA) and acetic acid (AA) contents at day 3 and 60 of ensiling. The final silage of FSm and MZm showed lower ( Ensiling is a traditional technique for the preservation of green forage in the livestock industry and a crucial method for conserving biomass before its anaerobic digestion . Silage Sorghum bicolor) is a C4 crop in the grass family that is introduced to livestock feeding due to its high biomass production and digestibility [Forage sorghum  did not improve the silage quality, while was only improved by the natural strains of epiphytic LAB (P. acidilactici GG13 and L. rhamnosus GG26) at such a high temperature by increasing the LA content and reducing the silage pH and butyric acid and ammonia-N content. These studies show that some commercial LAB inoculants under high-temperature conditions may provide partial support to improve the silage fermentation quality, whereas the natural strains of epiphytic LAB may have higher adaptability.In general, LAB inocula are suggested as silage additives to preserve the nutritive value of ensiled forages when conditions compromise adequate fermentation . It has m et al.  reportedEpiphytic lactic acid bacteria as pre-fermented juices (PFJLB) have been utilized in the past to enhance the silage fermentation quality of various forages ,15. HoweForage sorghum, maize, Napier grass, and Sudan grass were grown at the Nanjing Agricultural University’s Baima Research Station in Jiangsu Province, China. Forage sorghum was manually harvested at the dough stage of maturity (at about 27.8% DM), while Napier grass was picked at the vegetative maturity phase (at about 24.2% DM) after 60 days of regrowth. Sudan grass was picked at the milk phase after achieving DM contents of 24.8%. Maize was cut at the half milk-line phase (27.2% DM). For making silage, forage sorghum was cut into a size of 2–3 cm via chopper .g for 90 min. After discarding the supernatant, the residual pellets were re-suspended in 54 mL of the sterile saline solution.The epiphytic microbiota of the four forages was extracted in line with the method described in a previous study  with min60Co source according to our previous study [About 500 g of cut forage sorghum after proper mixing was filled in 40 × 25 cm polyethylene plastic silo bags. Overall, 90 silos (6 ensiling days × 5 treatments × 3 repetitions) were treated with gamma irradiation at 32 KGY for 2 h by using a us study . The curus study .The sterilized silo bags after gamma irradiation were treated as follows: (i) sterilized water (ST); (ii) microbiota of forage sorghum (FSm); (iii) microbiota of Sudan grass (SDm); (iv) microbiota of Napier grass (NPm); (v) microbiota of maize (MZm). A 3 mL volume of sterilized water or epiphytic microbiota (inoculum) was added to individually sterile silo bags in a laminar flow hood, evading contamination. A 3 mL inoculum volume for 500 g of silos was adjusted according to the formulation reported in a previous study . All of 3–N) concentration, pH value, and ethanol and organic acids contents. The pH value and concentration of NH3–N of the extract were assessed following the protocol described in a previous study [Three silos for every treatment were opened and thoroughly mixed in separate ethanol decontaminated plastic containers. Three representative samples from each box were taken to assess fermentation products and microbial count. The first 30 g of subsample was diluted with 70 mL sterilized water and preserved for 24 h, at 4 °C. Thereafter, the homogenate was filtered through two-layered medical gauze and a layer of Whatman filter paper. The liquid extracts were used for the determination of ammonia nitrogen  , whereasg for 15 min to make a pellet for DNA extraction. Following the manufacturer’s instructions, the Fast DNA®® SPIN Kit and Fast Prep®® Instrument  were used for the extraction of bacterial DNA from the inoculum and silage samples. To investigate the bacterial dynamics and composition during the initial and late stages of silage fermentation, day 3 and 60 ensilage samples from all of the treatments were chosen for high throughput sequencing. Polymerase chain reaction (PCR) was applied to amplify DNA, with primers 338F and 806R directing the V3-V4 sections of 16S rRNA genes [The previously stored water extract was normalized, at 4 °C, before centrifugation at 10,000× NA genes . Quanti https://drive5.com/uparse/, accessed on 26 July 2022) was used to cluster the operational taxonomic units (OTUs) with a sequence similarity of 97 percent [http://rdp.cme.msu.edu/, accessed on 26 July 2022) were used to examine the taxonomy of every 16S rRNA gene sequence using a 70% degree of confidence threshold. Mothur  was used for calculation of the alpha diversity, mainly the Chao1, Good’s coverage and Shannon index, of the sample [Majorbio Bio-Pharm Technology Co., Ltd. employed the Illumina MiSeq PE 300 platform for DNA sample paired-end sequencing . For eliminating any confusing readings and raw sequences from the primers, high-quality clean reads were obtained. UCHIME confirmed and separated the chimeric sequences. The UPARSE pipeline .The MIXED SAS technique was used for statistical data analysis in a factorial design . One-way analysis of variance (ANOVA) was used for comparing the chemical contents and microbiological populations of sterilized and fresh forage sorghum before ensiling. The silage fermentation value and microbiological compositions of silage were studied by using two-way ANOVA. The values were considered statistically significant at 10 CFU/g FW, respectively. Microbial growth was not identified in sterile forage sorghum in this investigation. There were no significant effects detected in the chemical structure of sterilized and unsterilized forage samples.The chemical structure and microbial compositions of sterilized and unsterilized forage sorghum prior to ensiling are shown in p < 0.05) the pH value, ratio of LA/AA content, and values of LA and AA contents (p < 0.05) LA concentration compared to other treatments. A significantly higher concentration of AA was observed in NPm and SDm silages after 60 days of ensiling compared to the MZm and FSm silages. Compared to the other treatment silages, the FSm and MZm silages showed a lower (p < 0.05) pH value, AA, and LA proportions after 60 days of ensiling. During 7 and 15 days of ensiling, the LA/AA ratio for MZm silage was higher; however; during the terminal ensiling, the LA/AA ratio for FSm and MZm inoculated silage was higher (p < 0.05) than for other silage. In all treated silage groups, the ethanol concentrations increased as ensiling progressed (p < 0.05) ethanol concentrations after 60 days of ensiling than NPm and SDm inoculated silages.The treatments, ensiling days, and their interaction altered (contents . With progressed . FSm andp < 0.05) the DM, NH3–N, and WSC contents are shown in p < 0.05) after 60 days of ensiling than other silages. In each silage, the NH3–N content increased as ensiling progressed. However, compared to the treated silages, the NH3–N content of ST silage was much lower. The NH3–N content was lower (p < 0.05) for MZm silage compared to the other treatments during the terminal ensiling. The number of LABs increased after ensiling in inoculated silages, but Enterobacteriaceae and yeast numbers decreased (10CFU/g FW) after 3 days of ensiling. The population of yeasts in all silages decreased as ensiling progressed. The MZm silage has higher yeast counts during the early ensiling compared to the other silages; however, ensiling depressed their growth.The results of the effect of different epiphytic microbiota sources and ensiling duration affecting (ecreased . All inoAcinetobacter was predominantly present in the NPm (37.4%) and SDm (25.6%) inoculums, whereas Enterobacter was abundant in the MZm (32.8%) and FSm (35.9%) inoculums. Statistical analysis of the bacterial composition on the genera level (10 most present genera) also shows that the genera of Acinetobacter were significantly (p < 0.05) higher in NPm and SDm inoculum while Enterobacter was predominantly present in MZm and FSm inoculum (Weissella (50.6%) and Lactococcus (43.5%) bacteria on day 3 of ensilage, while FSm-treated ensilage was composed of Weissella (65.5%) and Lactobacillus bacteria (27.9%). On day 3 of ensilage, bacterial species in NPm silage were primarily composed of Weissella (55.4%) and Lactococcus (38.6%), while Lactococcus (55.2%) was the prominent bacterial genera in MZm-inoculated silage. One-way analysis of bacterial genera evaluated that Weissella were significantly (p < 0.05) lower while Lactococcus was higher in the 3-day MZm-treated silage  in MZm silage. Lactococcus are homofermentative LAB and contribute to the higher LA production during fermentation [As the silo becomes anaerobic, the LAB quickly propagates and converts the available sugar to organic acids, chiefly LA resulting in the reduction in the silage pH value . Likewisondition . The higla genus . The higentation . The valentation . Ethanolentation .2). The extent of DM loss during the fermentation could be influenced by the dominant microbial species and the substrates fermented. There was no decline in DM during homofermentation by LAB, which ferments glucose and yields only lactate, while LAB ferments glucose heterofermentatively and produces 1 mole of CO2 for each mole of glucose during heterofermentation, resulting in a 24% DM loss [p < 0.05) in DM contents and WSC in the inoculated silage could be due to the presence of heterofermentative LAB species which ferment the available sugar contents heterofermentatively. The absence of microorganisms in the ST group could be the possible reason for the high DM and WSC content than the inoculated silages. During fermentation, NH3–N is formed through proteolytic clostridial species and plant protease activity [p < 0.05) NH3–N concentration during the terminal ensiling of MZm silages.During anaerobiosis, numerous anaerobic and facultative microorganisms proliferate and primarily ferment sugars and organic acids in forage . The los DM loss . The decactivity . The NH3activity . In the Enterobacteriaceae and yeast decreased in inoculated silages  after 3 days of ensiling, which could be related to the fall in pH value, which severely impacts the growth and viability of Enterobacteriaceae in silage [LAB, enterobacteria, molds, and yeast are common forage epiphytic microbiota detected during ensiling. However, following ensiling, the fermentation process particularly supports the proliferation of LAB species . The pop silages . The coun silage . The red< 2.0 logCFU/g FW Except for MZm silages, the OTUs counts and also the Shannon and chao1 indices decreased over 3 days of ensilage in the current study. During the anaerobic fermentation condition, the different epiphytic microorganisms, other than LAB, may be inhibited and inactivated , and thiAcinetobacter were significantly (p < 0.05) higher in NPm and SDm inoculum, while Enterobacter was predominantly present in MZm and FSm inoculum. In contrast, Duniere et al. [In the present study, the abundance of epiphytic microorganisms varies among the different forage sources. The e et al.  found the et al. . Howevere et al. . Correspe et al.  also demLactococcus, Weissella, Leuconostoc, and Pediococcus are more active during the early ensiling and greatly decline the silage pH [Lactobacillus can withstand a wide range of acidic environments and dominate the advanced phases of ensiling [Weissella and Lactococcus genera, while the later stages of ensiling were dominated by Lactobacillus genera. The Weissella genera belong to the obligatory heterofermentative LAB and convert sugar into AA, LA, and CO2 during their fermentation [Weissella during the 3 days of ensiling. Lactococcus are homofermentative LAB genera and have a positive impact on silage fermentation value during the ensiling process [p < 0.05) LA amounts in MZm silage during 7 days of ensiling could be the reason for the abundance of Lactococcus genera during early ensiling. The increased LA/AA ratio for MZm silage on day 3, 7, and 15 of ensiling compared to other treatments could also be attributable to their higher Lactococcus genus abundance during the specified ensiling time.Generally, LAB genera of ilage pH . Howeverilage pH . In compensiling . Similarentation ,53. The  process . The greLactobacillus species. Heterofermentative Lactobacillus species could be the possible reason for the heterofermentation and higher AA production in Napier and Sudan grass microbiota inoculated silages. The present study evaluated the effect of exogenous epiphytic microbiota on the fermentation quality of tropical forage silage, which provided a theoretical basis for the selection of potentially efficient and environmentally friendly lactic acid bacteria additives for silage in tropical regions. Further study is recommended to investigate the forage epiphytic microbiota and silage microbiota on the species level which will provide insight into the forage epiphytic microbial community and the bacterial species responsible for the changes during the fermentation.The findings of the present study reveal that under similar environmental condition, different tropical forage species inhabit different types and proportion of epiphytic microorganisms. Different epiphytic microbiota appears to have an impact on the fermentation products as well as microbial population dynamics of silage. All of the four inoculated epiphytic microbiota performed well during the forage sorghum ensiling. Homofermentation in maize (MZm) and forage sorghum (FSm) microbiota inoculated silages prevailed due to the homofermentative