Evolutionary ethnobiology and cultural evolution: opportunities for research and dialog

Utilitarian redundancy is a concept that emerged in ethnobiology that is used to characterize the organization and dynamics of local ecological knowledge [7, 40‐45]. According to the utilitarian redundancy model, different biological resources may have the same utilitarian functions in a given social-ecological system. The redundancy of resources with the same function decreases the use pressure on the used species and increases the resilience of the social-ecological system (see [44]). For example, in local medical systems, some diseases may be treated by more than one resource, so these resources are redundant in terms of their therapeutic roles. Therefore, in the absence of one resource, another resource can be used in its place, which ensures the resiliency of the medical system and the maintenance of local health [40, 44]. This redundancy indicates a variation in traits within the same cultural domain, which is extremely important to the evolution of systems. We can draw a parallel to standing genetic variation, which shows that a species that maintains genetic variation at the same allele adapts faster [46, 47]. Therefore, standing variation has an important role in facilitating a swift adaptation to novel environments or rapid changes [47].

As previously mentioned, redundancies or trait variations in different cultural domains can voluntarily occur in cultural systems by guided variation. Guided variation, which Mesoudi [9] refers to as a Lamarckian microevolutionary process, occurs when information is intentionally modified by an individual to achieve a given objective. For example, someone learns about a palm tree species that is used to make a specific object, but then an environmental variation makes that species of palm tree unavailable at a particular time. This unavailability may cause the individual to use the original received information (i.e., the shape of the palm leaves) to experiment with using a similar species. In this way, the initial information a plant X can be used to make the object can be intentionally modified, which results in the addition of a new plant. Together with the original information, this new information may be transmitted and become part of a set of plants that is used by the community. This process of guided variation, when repeated several times, can increase the repertoire of useful plants for a given cultural domain. Therefore, as noted by Boyd and Richerson [12], guided variation does not depend on a previous variation in the population. Unlike the selection-like content and context biases, guided variation is related to an individual’s transformative trait and is unrelated to the cultural variants of other individuals.

However, the creation and recreation of a new trait can randomly occur through transmission errors or randomly generated innovations through a process known as cultural mutation [9]. These errors randomly occur, and the resulting damage or advantage of the modification is not perceived. When a given trait is transmitted multiple times, the probability that an error will occur increases; a higher frequency of knowledge transmission can generate noise in a similar manner to what occurs in the game of “Chinese Whispers.” This form of cultural mutation can also explain the results of ethnobiological studies of local medical systems that show a higher redundancy in medicinal plants that treat the most frequent diseases compared to those that treat infrequent diseases [7, 41]. These differences in treatment redundancy may occur because the higher frequency of the disease leads to a higher number of knowledge-transmission events regarding its treatment, which generates noise and becomes aggregated in the local pharmacopeia. In other words, the more times people have to transmit certain information, such as the treatment of a disease that occurs frequently, the more susceptible this information will be to random changes due to the same logic as that in the game of “Chinese Whispers.” However, the permanence of these errors is typically lower if they decrease the fitness of the population. If an error caused by cultural mutation decrease the fitness of the population, as in a case that leads to death, the local people will detect that the treatment information may not be useful and should be abandoned, even if the information is never perceived as the result of transmission errors. Thus, depending on the effect on the population’s fitness, this “erroneous” information can be eliminated, even if it is never perceived as the result of transmission errors. Relative to non-serious diseases, serious diseases often have fewer distinct medicinal plants that can be used for their treatments [7, 41], which may be due to the rapid elimination of variations in random treatment information when the threat to life is higher. For non-serious diseases, the errors may remain unidentified as errors because they have little impact on the population’s fitness. However, these explanations are mere assumptions because these ethnobiological studies do not focus on explaining the observed patterns within the cultural evolution framework. It is possible that these results simply show that fewer remedies are effective against serious diseases or that the frequency of the disease enables more experimental attempts with new medicinal plants, which increases the plant repertoire for frequent diseases. This observation highlights an adaptive characteristic in the local medical system. Thus, we must emphasize the importance of pursuing a more thorough analysis of these observations.

Migration is another source of cultural trait variations because it increases the trait variability within a culture by introducing new information [9, 13]. In CE, migration refers to both the migration of an individual who carries information from one place to another (i.e., demic diffusion) and the migration of the information itself (i.e., cultural diffusion) through other transmission pathways, such as books, radio, television, and the internet [9] (Table 3). Ethnobiological research contains numerous examples of cultural demic diffusion. These examples show that people carry with them the knowledge of their place of origin after migration and can exchange this information with people at the new site, adopt novel knowledge, and create variation [48‐51]. However, cultural differences can block the exchange of information, thereby preventing the increase in cultural variation [52, 53].

One example of a migration-associated variation is the introduction of an exotic species into a local pharmacopeia. By demic diffusion, a person migrates and carries a plant with him; by cultural diffusion, the person sees information about the plant on television or in a magazine and acquires it at a local market. Albuquerque [54] suggests that this introduction may involve the need to fill the treatment gaps that are left open by the native species. Therefore, a possible interpretation in CE is that migration creates variation, which fills the local cultural domains that were previously left open, or introduces variants that increase the local population’s fitness, which favors the fixation and spread of these new traits over time.

Another example of cultural migration that is widely studied in ethnobiology is the introduction of western medical systems, (i.e., healthcare centers where industrial drugs are available) into a local medical system that is based on medicinal plants and has different definitions of illnesses. Several studies have suggested that the presence of western medicine (information that migrates into the community) has a negative impact on preexisting medicinal information [55, 56]. However, these studies do not regard the evolutionary perspective, which might contribute to the interpretation of data. For example, if these drugs present an advantage to the population (i.e., by increasing its cultural or biological fitness) and if they are compatible with the preexisting system, they can coexist with the local medical system (see medical pluralism in [57, 58]). Other ethnobiological studies have introduced various new issues related to migration, though they have not originally approached the evolutionary issue (Table 4).

In addition to information variation, processes that favor the most beneficial traits within a range of diverse traits are necessary for culture to be adaptive (see [17]). Mathematical models indicate that the transmission of cultural traits must be selective. Otherwise, the added evolutionary benefit of a cultural system compared to an individual learning system would not be guaranteed [16]. In the aforementioned example of resource redundancy, some resources within a range of redundant but useful resources may be preferred over others [7, 40, 42, 44, 59]. From a CE perspective, this preference reflects the competition for expression; a preferred cultural trait is simply a more attractive trait in a given social-ecological system. When an individual indicates his preference for one useful species over another, it is because the information regarding this species is more competitively expressed than the information regarding the other species with the same function (redundant). The competition for expression will result in cultural selection, which results from biases in the memorization and copying of specific cultural traits.

Several types of biases have been described [9, 12, 39], and we can categorize them as content and context biases. Content biases consider the intrinsic attractiveness of a trait, which is usually predetermined by biological or prior cultural evolution [9, 13]. Context biases indicate that the copying of specific cultural traits depends on the learning environment, the learner’s condition/life experiences (i.e., the frequency of the trait in a population), or the success of the individual (model) who possesses the trait (i.e., success bias) [9, 39].

The ways in which content biases influence the dynamics of cultural traits in a population can be characterized by the intrinsic preferences of different groups when copying information, such as the preference for transmitting social information versus non-social information [60], the preference for transmitting information that evokes feelings of disgust [61], or the adaptive memory that forms when information is memorized [62, 63]. Adaptive memory is a form of memory that has evolved to help individuals remember useful and relevant information during decision-making processes, where information that is more advantageous in terms of adaptation is more easily memorized and recalled. The concept of adaptive memory is extremely relevant to EE research [2], and it describes why some traits become fixed in a population rather than others. However, differential fitness can vary between individuals or human groups, and a trait that appears more advantageous for one person or group is not necessarily adaptive in the cultural context for another person or group.

To explain content biases (i.e., the attractiveness of a cultural trait), Mesoudi [9] draws attention to what Rogers [64] calls “attributes of innovations and their rate of adoption.” According to Rogers [64], an innovation will be adopted if it is advantageous over other information, if it is compatible with the preexisting system, and if it is testable and observable to others. In ethnobiological studies, we can observe several characteristics of attractive cultural traits that focus on the drivers of preferences for information regarding useful plants. For example, an investigation of medicinal plant preferences by Ferreira Júnior et al. [42] shows that the preferred plant is the more effective one, which has an advantage over the less effective alternative. Santoro et al. [7] have supplemented these data with their observations that in the absence of the preferred medicinal species, the second- and third-ranked preferences are other medicinal plants, even when other remedy types for treatments exist, such as industrial drugs; this shows that biomedical information can be incompatible with medical systems and is less preferred. In a study of plants used for fuel, Ramos et al. [65] found that people may share more information regarding the plants with higher heating values (i.e., a higher number of transference events) than the plants with lower heating values (i.e., with low efficiencies of heat production).

These studies do not address preferences in the context of cultural evolution, and we can only assume that the preference characteristics indicate content biases. An important question that arises from these results is whether people are aware of their preference choices. For example, in a study of plants used for food, Henrich and Henrich [66] observe that pregnant women avoid dangerous fish, which can cause miscarriages, without explicitly understanding this link. They simply copy the information from other people (i.e., models, who are usually family members or experts) without understanding the reason for specifically avoiding the food. In this case, the copying behavior is not guided by content bias; it is guided by context. The reproductive state of the pregnant woman can be the context that biases the copying of information [39], but it is evident in this study that the context bias is model-based and dependent on the people who possess the information.

Some studies have shown that information transmission depends on models with high expertise [36, 67]. The selection of the model to be copied usually occurs before the content of the information and its advantages and disadvantages are known [9]. In these cases, copying information from people with expertise in a particular field can be adaptive because expertise indicates that the person is a specialist or possesses great knowledge on the subject. For example, in a society that is sustained by hunting, the best way to learn about hunting is by copying the actions of the hunters with the most knowledge because they can direct the best strategies to guarantee successful hunting. However, the information source is often unrelated to the information that is copied. People may perceive a person’s success in a specific field and begin copying cultural traits from this person that are associated with other fields through an associative process [36]. For example, people who accumulate high expertise in a community by being good fishermen may be copied in other domains of knowledge, such as crop cultivation (see [36]).

Model-based context is not always guided by expertise; it can be age-based (preference for copying people of a specific age), gender-based (preference for copying women or men), kin-based (preference for copying family members), and so on (see [39]). In the context of medicinal plant information, ethnobiological studies have shown that people mostly acquire knowledge at home with their parents [5, 6, 68‐70], which may indicate the importance of the kin-based model bias in local medical systems. Additionally, the ethnobiological literature is replete with examples that show differences in the local ecological knowledge between people of different ages (where older people have more knowledge than younger people) [71, 72], education level (where a high education level is associated with less ecological knowledge) [73] and gender (where women have more knowledge on specific cultural contexts while men have it on others) [73‐78]. These parameters can also be used to verify a group’s tendency to use models from a particular gender, age, or educational level for copying information. Table 4 presents several possible questions that arise from these studies. For example, Pfeiffer and Butz [79] suggest that when knowledge differences exist between genders, the knowledge variations can be strongly influenced by transmission of the knowledge between the genders and by gender-based differences in the social network, which can be explained by the model-based bias of gender dependence.

When there is no clear incentive toward or advantage to copy one trait or one good model over another, people tend to copy information that is shared by the majority of people in a population [13, 80‐82]. This tendency is called frequency-dependent or conformity bias [9, 13] and assumes that if a person does not know how to behave, it is more advantageous to behave in a similar manner as the majority. For example, an individual may prefer to copy a more common house structure when building a house in a rural community because he does not know the most effective of all the available possibilities. Here, he can see that a relatively large number of successfully built houses in this rural community indicate that the probability that this particular house structure will fall is low. Conformity bias can be observed when the copy frequency of the majority exceeds what is probabilistically expected by randomly copying the behavior [13]. The opposite of this tendency is anti-conformity, when people prioritize copying the least disseminated cultural trait in a population.

It is important to note that the fixation, extinction, or variation in the frequency of cultural traits can occur both by competition and selection of traits and by chance, in a process known as cultural drift, which is analogous to genetic drift. These traits can be introduced into a population by random variation, guided variation, or migration; they do not undergo any form of selection, but they vary widely in frequency, which results in their fixation or elimination [9]. Like genetic drift, cultural drift is a more important process in smaller populations because chance-sampling accidents are more probable. However, the occurrence of cultural drift in human groups appears unlikely because many cultural trait variation dynamics are guided, and there are several cognitive and psychological biases that influence the choices that are made at the time of transmission; however, some studies have shown that several cultural traits are randomly distributed within populations [83, 84].

Cultural transmission may be the main microevolutionary process of interest in ethnobiology (i.e., [5, 6, 56, 69, 70]). However, these studies present different viewpoints regarding teaching and learning, which specifically result in methodological and analytical differences.

Several studies have characterized learning as a complex process in which individuals become competent at a given cultural skill. For example, Bock [85] observes that the development of competency for a specific task occurs from an energy investment trade-off between the development of body characteristics and the investment in learning experiences. This perspective is similar to the learning model that is proposed by Ruddle and Chesterfield [86], which describes that the learning of a complex skill occurs through a sequence of different tasks, which begin with the simple tasks that are mediated by trial-and-error events. Other studies have analyzed learning as the result of specific events of information transference (see [5, 69]). For example, Soldati et al. [6] have investigated whether learning strategies are influenced by the characteristics of the environment where people live; they address the initial assumption that learning occurs during specific events over the informants’ lifetimes, and they have quantified this information.

Because CE is an approach that originates from mathematical models of population genetics and epidemiology (see [9, 22]), it emphasizes the importance of the frequency of information within a population. Therefore, CE indicates that the specific acquisition of information (cultural traits) should be prioritized over the process of becoming more proficient in a given skill. These broad-level transmission pathways are easier to model than skill proficiency, and CE favors the construction of testable models and hypotheses regarding cultural transmission.

As previously mentioned, parent-to-offspring cultural transmission may not always occur. Mesoudi [9] has subdivided cultural transmission into the following three distinct pathways: (1) from the parents to the offspring (vertical), (2) between unrelated members of the same generation (horizontal), and (3) between unrelated members of different generations (oblique). The scopes of the distinct transmission pathways are related to their possible spread. For example, the horizontal and oblique pathways have a higher scope than the vertical pathway because they allow the transmission of traits between all individuals of the same generation or of different generations [9]. Hewlett and Cavalli-Sforza [27] have subdivided these pathways into the following two types: “one-to-many” and “many-to-one.” In “one-to-many” transmission, traits are transmitted from a model, such as a teacher, leader, or the media (television or radio), to multiple individuals in one group, who are usually students or apprentices. In “many-to-one” transmission, the typically older members of the social group teach one selected individual. However, the scope of vertical transmission is limited to the number of offspring of a given parent [13] and can often be “one-to-one” transmission (Table 3).

Ethnobiological studies have found that the cultural traits of medical systems are mainly transmitted through vertical transmission [5, 6, 68‐70]. This form of transmission suggests that plant medicinal resource information varies little over time. Vertical transmission is typically more conserved because transmission from parents to offspring only results in the accumulation of changes from one generation to the next. However, the horizontal and oblique pathways have wider scopes and can promote quick changes, which are often observed in the cultural trait changes that result from knowledge transmission from the media.

The method that is used to collect the data regarding an information transmission pathway should be chosen carefully. For example, people tend to overestimate their learning from parents when simply asked about who taught them about medicinal plants [70, 87‐89]. Several studies of vertical transmission have suggested that although the information may have been perfected through horizontal or oblique pathways during the informants’ lifetimes (an essential process in the dynamics of local knowledge), the informants may have only referred to their first contact with the medicines, which often occurred during childhood [36].

In addition to the transmission pathway and scope, an important aspect of the study of cultural transmission within a CE framework is the transmission mechanism. According to Mesoudi [9], cultural traits can be transmitted through a particulate mechanism, where a trait is transmitted completely from one person to another, or through blending, where one individual can simultaneously adopt different proportions of two competing traits (Table 3). The particulate mechanism resembles what occurs with gene transmission, where information is transmitted by discrete units. One example is the information that plant X can be used as fuel for fire pits. People can faithfully transmit this information to one another without interference from another source. The approach of discrete units of cultural information has been widely used in memetics [10], where cultural evolution can be viewed through a neo-Darwinian perspective.

The blending mechanism can be better understood by considering the transformative process through which cultural information is transmitted; the transmission reflects a variation gradient, whereby each trait can be expressed to a varying degree. Transmission by blending is similar to the transmission that occurs for phenotypic variations, in that intermediate phenotypes result from the partial dominance of one gene or the co-dominance of two genes [90]. People usually blend cultural information from various sources before they transmit it to other people. An example of cultural transmission by blending is the belief system of an indigenous group after being colonized and its subsequent acquisition of information regarding Christianity, which resulted in a generation of new religious doctrines through the blending of original indigenous beliefs with Christian dogmas. Nevertheless, we believe that even continuous variation that is caused by blended transmission can be analyzed as discrete units in specific cases. For example, the blending of indigenous and Christian beliefs can be studied as a particulate mechanism; people can adopt a set of binary traits from the Christian belief system and maintain the indigenous beliefs for other traits. This phenomenon is frequently observed with syncretism. Furthermore, for the statistical analysis, it is helpful to divide a continuous variation into discrete categories (i.e., divide the continuous scale into “high,” “medium,” and “low”), but whether the loss of information is worth the advantage of analyzing discrete data remains unclear. Nevertheless, it is necessary to collect large amounts of continuous data to observe this type of blending as a particulate mechanism.

This article is not intended to deepen the polemic between the vision of cultural transmission as a preservative mechanism, where discrete traits are transmitted with high fidelity and the vision that information is reconstructed each time; it is transmitted as a result of blending (for this discussion, see [14]). However, we must clarify that we do not favor the neo-Darwinian perspective in the understanding of cultural evolution; we prefer the Darwinian perspective. Therefore, a cultural trait (discrete or not) is one aspect of the human phenotype and is the basis for the analysis of human evolution (see [18]). However, evolution occurs at the level of the organism and is not based on the replicator, whether it is a gene or a cultural trait. Thus, ethnobiological studies usually focus on particulate transmission because it is often difficult, if not impossible, to collect and analyze large amounts of continuous data, such as that for traits that are transmitted by blending. A well-studied example is the particulate transmission of discrete “plant-therapeutic treatment” traits in the studies of medicinal plants.