Population Genetic Structure: Where, What, and Why?

Abstract

Biodiversity is crucial for humankind. It encompasses three main levels: ecosystem, species, and intraspecific genetic diversity. Species consist of populations that exhibit deoxyribonucleic acid (DNA) variability, which is a key component of intraspecific genetic diversity. In turn, intraspecific genetic diversity is directly linked with the term population genetic structure (PGS). There is a great deal of uncertainty and confusion surrounding the concept of the PGS of species in the scientific literature, yet the term PGS is central to population genetics, and future research is expected to focus on the evolutionary continuum from populations to species. Therefore, it is necessary for current biologists and the next generation of scientists to acquire a better understanding of a PGS, both as a term and a concept, as well as the various roles PGSs play within a biodiversity context. This knowledge can then be applied to the expansion of both practical and theoretical science. Finding answers and reaching a consensus among the scientific community on certain questions regarding PGSs could expand the horizons of population genetics and related research disciplines. The major areas of interest and research are PGSs’ roles in the processes of microevolution and speciation, the sustainable use of natural resources, and the conservation of genetic diversity. Other important aspects of this perspective review include proposals for scientific definitions of some terms and concepts, as well as new perspectives and explanations that could be used as a basis for future theoretical models and applied research on PGSs. In conclusion, a PGS should be viewed as a fragile genetic mosaic encompassing at least three spatial dimensions and one temporal dimension.

1. Introduction

The Anthropocene (for readers’ convenience, major terms (bold text) and abbreviations could be found in the lists in the Supplementary Materials document Glossary-Abbrev S1) has had a complex impact on biodiversity as well as an interesting relationship with it. On the one hand, advances in technology, such as ancient DNA (aDNA), one of many modern scientific applications that were not feasible just 20 years ago, now allow scientists to study past populations and understand how populations are changing today in ways that may reduce harm (see [1] and the references therein). On the other hand, the ongoing adverse anthropogenic impacts on most natural habitats present a potentially catastrophic and irreversible threat to global freshwater environments and the species, including humans, reliant upon them [2]. The modern consensus is that despite the high fecundity of many fish species, this trait is not sufficient for maintaining a sustainable stock under intensive harvesting, and current predictions suggest fish stocks may become exhausted by 2050 (see [3] and the references therein). This situation gives rise to the following questions: can life be understood without the concept of biodiversity [4,5,6], and can we sustainably exploit [7,8] or protect [9,10] life systems without comprehensive knowledge of the processes occurring within ecosystems and species [11,12]?

International agreements recognize biodiversity at three fundamental levels: ecosystem diversity, species (interspecific) diversity, and within-species (intraspecific) genetic diversity (see [13] and the link provided therein). As fundamental units of conservation, species are often used to quantify biodiversity through lists of species within protected areas, to identify threatened species within jurisdictions, and as the basis for biosecurity procedures [14]. Unfortunately, there are many ways to distinguish species [15], creating additional problems for scientists (especially taxonomists), legislators, and managers [16]. Researchers have proposed over two dozen distinct concepts of species, and there is still no universal concept for all organisms. The most widely used concepts of species include the Biological Species Concept (BSC), which is based on reproductive isolation; the Morphological Species Concept (MSC), which is based on physical traits; the Ecological Species Concept (ESC), which is based on niche differences; the Phylogenetic Species Concept (PSC), which is based on monophyly and diagnosability; the Evolutionary Species Concept (EvSC), which is based on lineage continuity; and the Genetic Species Concept (GSC), which is based on genetic similarity or distance [17]. The most widely accepted concept, the BSC, has limited applicability or is inapplicable to asexual organisms, fossils, hybridizing and ring species, and geographically isolated populations. Thus, it has been challenged many times (see [18] and the references therein), and it is still considered questionable [19]. Critically, the choice of which concept of species to apply can depend on various factors, such as research goals, available data, and context. It is often the case that different concepts are useful in different situations, and using multiple species concepts together can provide a deeper understanding of biodiversity and evolution, yet it is important to avoid possible confusion among researchers by clearly defining the concepts used during research.

Even if conservation management actions, especially those based on strategies designed to improve environmental conditions, succeed in slowing, halting, or reversing genetic diversity decline, genetic diversity loss may still be recorded, so it is not surprising that genetic diversity loss is occurring globally in the 21st century. Consequently, without necessary, rational actions undertaken by humans, the degradation of intraspecific genetic diversity will ultimately lead to extinction; this is a realistic prediction for many species in the face of threats such as land use change, disease, abiotic natural phenomena, and harvesting or harassment [13]. Several years ago, Coates et al. [14] rightfully stated that current approaches to biodiversity conservation are largely based on geographic areas, ecosystems, ecological communities, and species, with less attention paid to intraspecific genetic diversity and the evolutionary continuum from populations to species. Yet, in 2025, it now seems that the situation is shifting toward the creation and application of better strategies to improve the protection and management of this essential level of biodiversity. If we want to focus on species genetic diversity and the evolutionary continuum from populations to species, then gaining a better understanding of the population genetic structure (PGS) [20,21] of species is a rational, strategic, and crucial step forward. In this regard, it is important to remember that the development and advancement of genetic diversity indicators constitute a complimentary approach to genetic studies in conservation biology, not a substitute [21]. It is even more important to realize that while genetic diversity can sometimes be evaluated using some indirect methods, direct genetic analyses are necessary for obtaining conclusions regarding a PGS. Thus, depicting the population genetic structure of a particular species over a specific geographic region always requires genetic studies using some form of genetic markers [7].

Unfortunately, there is a great deal of uncertainty and confusion regarding PGSs in scientific literature. There are synonyms for PGS that may be encountered in the literature: genetic population structure [22,23], genetic structure [24], intraspecific genetic structure (see [25] and the references therein), and population structure [26,27,28]. Because populations can have different structures [29], one common synonym for PGS, namely, ‘population structure,’ should be avoided, especially when no appropriate context is provided. In some cases, researchers use terms such as ‘structure’ or ‘genetic structuring’ instead of explicitly referring to a PGS, yet the context typically makes the intended meaning clear [30,31]. In addition to the confusion surrounding the term PGS, there is no clear and globally accepted system (with several exceptions and attempts) for describing certain types of PGSs. Thus, based on the literature, a PGS can be defined as limited [32], weak [33], strong [34], cryptic [35], stable [36], hierarchical [37], mosaic [38], native [39], or genomic [40]. A PGS can be described using various combinations of these and other definitions, even within the same study [41].

The uncertainties regarding PGSs require a solution. That is, clarifications which could also be combined with a comprehensive revision and update are needed as, in science, it is often reasonable to systemize or even synthetize the already available and most recent information [6,28,42]. Both literature reviews and different creative scientific perspectives enable easier expansion and tracking of the progress of research fields [15,43], especially after some time has passed, at which point there is a need to evaluate what has been achieved, update our knowledge [10,44] and, occasionally, even trigger a paradigm shift [45,46]. While constantly improving Artificial Intelligence (AI) can certainly help to effectively systemize scientific information, only humans can provide new, creative, and valuable perspectives that not only transfer knowledge to readers but also inspire their creativity and motivate them to share their own opinions and perspectives.

The major goal of this work was to initiate the process of a comprehensive synthesis, as well as a rethinking, of the currently available information about PGSs. Thus, we creatively present to the interested scientific community what we already know and can expect in the future. Indeed, this perspective review is an attempt to ask questions concerning PGSs, find answers to them, and reveal scientific knowledge gaps that should be discussed and addressed by scientists. In addition, we also aimed to reduce the confusion in the scientific literature so that accumulated knowledge about PGSs can be transmitted more easily to the next generation of researchers and managers, thereby propelling PGS research even further. In general, we focus mostly on the PGS of eukaryotes, but most principles could also be applied to bacteria or even viruses. Special emphasis will be placed on the PGSs of certain species or organisms living in certain environments and conditions (for instance, aquatic life, especially taxonomically related fish species).

2. Where?

Biologists and managers with knowledge about ecosystems or their parts, especially in terms of practical cognition, quite often want to ensure that new information derived from other scientific disciplines is indeed relevant and, most importantly, transferable via a familiar basis of understanding that is already possessed to make others interested and curious. Consequently, we begin our scientific explanatory journey with the question ‘where?’. The question ‘what?’ will be answered later, in the third section.

The concept of species is crucial for defining both populations and PGSs. The term ‘population genetic structure’ implies that it should concern populations and be found within a population. In short, that is the case, yet without longer detailed elaborations of the places and roles of PGSs in populations, species and ecosystems would be oversimplified and inadequately understood within ecological contexts and frameworks. Therefore, to present the ecological context and avoid possible confusion, it would be wise to define crucial ecological and genetic terms (see Glossary S1 in the Supplementary Materials) and concepts, starting with species concepts and the question ‘What is a population?’.

2.1. Species Concepts

The concept of species remains problematic and is one of the most debated issues among scientists, particularly those working in evolutionary biology, taxonomy, ecology, and genetics. Clear species boundaries are also essential in applied fields, such as medicine, veterinary science, agriculture, food safety, conservation biology, biotechnology, and pharmacology, where decisions and interventions often rely on well-defined species delimitations. Therefore, any research on intraspecific structure should be grounded in a well-founded species concept or delimitation framework. To date, researchers have proposed more than 25 different concepts of species, some of the most widely used of which are summarized in

Table 1. Comparison of commonly used species concepts in terms of key features, temporal orientation, applicability to asexual organisms, and ontological status.

Species Concept	Key Features	Temporal Focus	Asexual?	Ontology	Ref.
Biological (BSC)	Reproductive isolation	Horizontal	No	Realistic	[47,48]
Cohesion	Maintained by gene flow and demographic exchangeability	Horizontal	No	Realistic	[49]
Recognition	Defined by mating-recognition systems	Horizontal	No	Realistic	[50]
Ecological (ESC)	Species occupy unique ecological niches	Horizontal	Yes	Realistic	[51]
Genetic (GSC)	Measurable genetic differences (allele frequencies, nucleotide sequence divergence, etc.)	Horizontal	Yes	Realistic	[52,53]
Morphological (MSC)	Shared physical traits	Horizontal	Yes	Operational	[54]
Phenetic	Grouped by overall similarity of traits	Horizontal	Yes	Operational	[55]
Genotypic Cluster	Clusters of genetically similar individuals	Horizontal	Yes	Operational	[56]
Polythetic	Overlapping sets of traits with no single defining feature	Horizontal	Yes	Operational	[57]
Taxonomic	Based on expert judgment and multiple criteria (e.g., morphology, ecology, and genetics)	Horizontal	Yes	Pragmatic	[58]
OTU (Operational)	Defined by sequence similarity thresholds (e.g., 97%)	Horizontal	Yes	Pragmatic	[59,60]
Cladistic	Based on shared derived characters	Vertical	Yes	Realistic	[61]
Evolutionary (EvSC)	Lineages with their own evolutionary tendencies and fates	Vertical	Yes	Realistic	[62]
Phylogenetic (PSC)	Smallest diagnosable monophyletic group sharing a common ancestor	Vertical	Yes	Realistic	[63,64]

.

Species concepts can be broadly categorized into horizontal and vertical approaches. Horizontal concepts, which are more numerous, focus on what is happening at present, such as population morphology, behavior, and distribution (e.g., biological, ecological, cohesion-based, phenetic, and recognition-based species concepts). Vertical concepts, on the other hand, emphasize how species evolve over time, prioritizing historical and evolutionary aspects (e.g., phylogenetic, evolutionary, and cladistic species concepts). Another important consideration is whether a species concept can be applied to asexually reproducing organisms, as many concepts employ sexual reproduction as a criterion for species boundaries. From an ontological perspective, species concepts can be categorized as realistic, operational, or pragmatic. Realistic concepts assume that species are natural entities that exist independently of human observation. Operational concepts emphasize observable and measurable criteria to identify species in practice, regardless of their ontological status. Pragmatic concepts treat species as practical constructs defined for specific scientific or regulatory purposes, prioritizing usefulness over theoretical rigor.

The most commonly used species concept is the BSC, which defines species as groups of interbreeding populations that are reproductively isolated from other such groups (see [47,48]). According to the BSC, a species functions as a reproductive unit (i.e., populations of different species are reproductively isolated because of physical or physiological barriers or natural isolating mechanisms), a population unit (a species consists of populations rather than individuals), and a genetic unit (the gene pool of a species represents an integrated set of co-adapted genes; reproductive isolation preserves the integrity of the gene pool, while interspecific hybridization can disrupt it). In addition to the BSC, several other species concepts are frequently applied across different biological disciplines. The MSC defines species according to observable structural features and is particularly useful in paleontology and classical taxonomy [54]. The ESC distinguishes species according to their ecological niches, emphasizing adaptation to different environments [51]. The PSC describes species as the smallest monophyletic groups that can be diagnosed via unique, derived characteristics; it is widely used in molecular systematics [63,64]. The EvSC defines species as distinct lineages of ancestral and descendant populations that maintain their identity and evolutionary trajectory over time [62]. Finally, there is the GSC, which defines species in terms of genetic similarity or dissimilarity, often using quantitative thresholds of molecular differences to identify independently evolving lineages [52,53].

In this paper, we do not seek to propose a novel concept of species; rather, we adopt the widely used, though imperfect, BSC, which aligns well with population genetics theory by defining species based on reproductive isolation and gene flow as fundamental processes that govern genetic diversity within and between populations. Nonetheless, species delimitation remains a dynamic field requiring ongoing refinement and focused attention. Accordingly, we tentatively define a species as a group of organisms exhibiting a high degree of phenetic, ecological, and genetic similarity; distinguishable from related groups; and constituting a distinct evolutionary lineage characterized by its own historical continuity and evolutionary trajectory.

2.2. Population

Many scientific books, articles, and other forms of literature conceptualizing the term population and its various aspects already exist (see [65,66,67] and the references therein). In addition, these types of literature continue to rapidly increase in number each year. Thus, we will mention only the most important aspects of population that are necessary for a proper understanding and definition of a PGS. In general, the term population is used in various ways to convey concepts that are important across many biological fields, but certain usages of the term can lead to ambiguity and misinterpretation (see [68] and the references therein). In ecology, a population is considered a fundamental unit and, in the corresponding scientific literature, a population of a species is typically defined as a group of individuals or objects sharing one or more common characteristics. Yet different fields refine this definition according to their specific objectives, and, as with many basic ecological concepts, the term population has been defined and applied in diverse ways, with no single definition having been proven to be fully satisfactory for all biologists (see [69] and the references therein). This basic common definition of population is not ideal but will suffice to allow one to understand the following paragraphs, especially after a small modification: a population is a group of individuals of the same species (according to the BSC) that are more related to each other through their major bio–ecological–genetic characteristics than other groups of individuals from the same or different species.

2.2.1. Population’s Role in Evolution and the Major Ecological Relationships Between Populations

In the scientific community, it is widely accepted that populations, not species, are the smallest units of evolution [70,71]. Modern evolutionary synthesis indicates that gradual changes in characteristics can be understood through changes in genetic diversity [72]. Consequently, microevolution (small evolutionary changes in populations over a relatively short period of time) begins in a population, and this process is mainly triggered by so-called evolutionary forces [23,27] (these forces will be presented in more detail in the subchapter 3.2.2), which are the major research objects of population genetics [73].

Each species consists of at least one population [32], and different demographic processes can occur in different populations [74]. Same-species populations can be connected by various symmetries and degrees because of their members’ migrations (see [75] and the references therein). Usually, asymmetrical migrations from larger populations to smaller ones occur [76]. Various ecological intraspecific relationships exist among and within populations or even their smaller parts (called subpopulations) [77]. Perhaps, the most common among those relationships are direct or indirect competition (see [78] and the references therein). Different populations of distinct species can have even more direct ecological relationships, such as interspecific competition (see [79] and the references therein), parasitism [80], predator–prey dynamics [81], or mutualism [82]; not to mention indirect relationships, such as producents creating oxygen for other life forms to exist [83] or successions forming new ecosystems over time [84].

2.2.2. Population Size

Typically, the number of reproductively mature individuals in a population is defined by the term census size (N_c) [85]. An infinitely large population has a large N_c but exists only in abstractions and theory, especially in the theoretical framework of population genetics (see [86] and the references therein), whereas in the real world, populations can be large, yet they grow only to a certain degree because of the so-called carrying capacity phenomenon [87]. Strier & Ives [88] suggest that the carrying capacity should be defined as the population size at which, on average, birth rates equal death rates, and carrying capacity should not be limited to resource availability but instead encompass all factors that affect birth and death rates and how these demographic rates change with population density. Importantly, different species and their populations may achieve this state in different ways, as each case is unique: every species has distinct biological characteristics and occupies a specific environment. This means that direct interspecific quantitative comparisons could be misleading, yet intraspecific quantitative comparisons would be reasonable. Population growth control is achieved naturally through both interspecific and intraspecific regulatory mechanisms [89,90]. Because a population can have a large N_c but only a relatively small number of reproducers can create a new generation (see [91] and the references therein); thus, a population is defined not only by its N_c but also by its effective population size (N_e). Theoretically, N_e is described as the size of the ideal population that would experience the same amount of genetic drift as the observed population. Practically, N_e is lower than N_c, and it refers to the number of individuals in a population who contribute offspring to the next generation. Both N_c and N_e are marked by decreases over time and described as examples of the bottleneck effect [92]. However, declines in the N_c of species with massive populations or very long-lived species might not lead to measurable losses of genetic diversity over the timescales studied [13]. Indeed, the delay between disturbance events and genetic responses within populations is a common but surprisingly overlooked phenomenon in ecology and evolutionary and conservation genetics: a time lag, which refers to delayed genetic consequences occurring after an environmental shift or population decline. If not accounted for when interpreting genetic data, this time lag problem can lead to erroneous conservation assessments [93]. Estimating N_c and N_e or original standing genetic diversity can be challenging, yet these two population-level parameters are imperative if we aim to, for example, reliably predict the rate and magnitude at which fisheries can induce a loss of genetic diversity [3]. A general representation of the complexity of estimating N_e can be found within the article by Fedorca et al. [85]. The most usual application is indirect estimates of N_e that are based on genetic parameters; this is because directly estimating N_e is typically impracticable as it would require knowledge about, among other things, the total number of individuals of a species and the variance in the lifetime of reproductive success among individuals [72]. Large populations in large distribution ranges have a large N_e and a reservoir of genetic diversity that can compensate for local genetic diversity losses (see [93] and the references therein). In contrast, small populations may enter an extinction vortex (see [94]), ultimately leading to their permanent disappearance from the Earth, surviving only in human memory. Owing to environmental change, especially due to anthropogenic influence, many species are now represented by fragmented populations [85]. For instance, agricultural intensification affects population connectivity among insects, especially pollinators, because of increasing habitat loss and pesticide use [23]. Indeed, large populations are continuously decreasing worldwide because of fragmentation, and the same natural laws and trends applicable to small populations affect fragmented populations—yet with a lower chance that these populations will experience an extinction vortex. The species with life history traits favoring time lags include perennial, long-lived plants, and other long-lived organisms such as sea turtles, which produce large numbers of unnurtured offspring, thereby combining the long life spans characterizing strict K-strategists with the high offspring numbers characterizing strict r-strategists [93].

2.2.3. Population Types

In general, populations can be categorized into many types based on various criteria. However, from the species-level perspective, only three main types of populations are usually described, serving as distinct and the most diverse structural units of species: panmictic populations [95,96], cases of two or more distinct populations within a species (see [97] and the references therein), and metapopulations [98]. Typically, a panmictic population is understood as being synonymous with a panmictic species, as it consists of only one large population, in which individuals from different locations have the same opportunities to randomly breed with other individuals from the same species [99]. However, this is not always the case in scientific literature. For example, conservation efforts remain complicated by persistent knowledge gaps associated with the white shark’s (Carcharodon carcharias) biology and ecology, including the biological connectedness of white shark populations, and the necessity of discussing panmictic populations in certain Australian regions within the broader context of this species having more than one population (see [32] and the references therein). Even species that are considered panmictic can surprise us with deviations from our theoretical assumptions. For instance, the famous and mysterious European eel (Anguilla anguilla) has been considered a panmictic species for a long time, yet this fish could have been reproductively isolated in small groups in its spawning ground [100], and this grouping could also be related to differences in sex behaviors [101]. Whether these small, isolated eel groups appear because of random factors is still discussed by scientists. Irrespective of the number of populations and their characteristics, populations are called distinct if at least two of them are structural units of certain species; that is, one species could comprise three populations and another could consist of four, and one species could have two large populations and one have an isolated small population, while another species could have small but connected populations, and so on. Scientists almost always have enough direct and indirect data to clearly define the smallest number of actually existing populations within a species, but the real numbers of all the existing populations within a species, or even geographic regions, are ambiguous and can only be assumed (see [32] and the references therein). The term metapopulation was coined in 1970 by Levins to describe a set of spatially discrete groups of individuals (see [68] and the references therein). Typically, in population genetics, a metapopulation is defined as a group of spatially separated populations of the same species that are connected by gene flow [85]. From now on, we can begin to look deeper within the major parts comprising populations and show the central place and role of a PGS within a proper context.

2.3. Population Structures

Scientists have long noticed great morphological diversity in animal and plants species and populations (see [102] and the references therein) and tried to use this diversity for practical research and the classification of living forms. Such efforts revealed that population morphological structure (PMS), comprising morphological variations [97,103,104] of individuals, is found in each population of each species [105]; that is, different individuals in populations have different body lengths, weights, and other meristic characteristics [106,107,108], including various distributions of scales on the bodies of fish [109] or the forms of feathers among birds [110].

2.3.1. Problematics of Population Morphological Structure

Sandberg et al. [111] tried to describe the essence of the problem of diversity within species in the following manner: it is noteworthy that once diving into the literature in search of examples of variation within species, the concepts used for describing this phenomenon are almost as varied as the thing itself. Thus, words such as ecotypes, subspecies, morphs, stocks, and varieties are common and essentially all refer to intraspecific variation. Clearly, similar tendencies apply at the population level as well, but that should not stop our attempts to better understand nature by providing different perspectives and creating and defining concepts, terms, and models. It is now known that populations of species of animals, plants, and other organisms comprise different interlinked structures (see Figure 1 and text below) because PMS must be divided into at least few distinct structures. This division is necessary (and rightly so) since even at the individual level, the overall morphology of a specimen is based on and determined by different underlying phenomena, constituting a combination of distinct processes. Indeed, the meristic characteristics of certain individuals could be related to different underlying phenomena, including phenotype [112], physiology [113], age [114], sex [10,115], and environment [108].

Phenotypes are targets of natural selection and affect the performance and diversification of organisms in variable environments [116]. Physiology can change individuals’ forms and weight during various biorhythm cycles occurring every day [117]. Age reflects the different life stages of an individual, and some lifeforms have many life stages that differ quite drastically from each other, allowing them to exploit different resources in their environments in different developmental stages. No one questions that the egg, the larva, the pupa, and the imago are all stages in the life of the same organism, e.g., a beetle, yet it is very difficult to say that they are the same thing. Thus, the organism itself is a process mainly because of this fact and two other reasons: first, an organism is a complex system far from thermodynamic equilibrium, so it should be seen as a life cycle; second, the vast majority of organisms exist in close contact with and extensively interact with numerous symbiotic partners (see [18] and the references therein). Many animal species are characterized by sexual dimorphism [118]; thus, different sexes appear in different shapes, sizes, and even behavior [119]. It has been discovered that the sex of marine organisms broadly affects the morphology, physiology, behavior, and distribution of organisms across taxa, with evidence of sex-specific differences in the ability to survive thermal stress, the timing of biological mechanisms, and energetics [10]. In many species, sex can largely be determined by the genetic programing of individual organisms, but there are species for which sex is determined more by the environment [120], especially with respect to temperature [121]. Environment also affects certain individuals’ shapes, sizes, and other parameters. For instance, one individual might be genetically programmed to be larger than others of its kind, but in a different environment, there may not be enough resources, potentially leading to a smaller individual.

Within a population, the situation is even more complicated. Thus, estimation and interpretation of meristic characters should be based on a precautionary approach (see [15,103]). Indeed, researchers could obtain results indicating that different individuals (or even groups) within a population have the same or similar meristic characteristics for several major reasons, including mistakes like human error and random factors [122].

The first reason is that certain measurable traits of phenotypes may be the same among certain individuals (see [104] and the references therein). Different classes of phenotypes vary in how they impact processes such as dispersal, colonization, and persistence, thus providing a window into the importance of various evolutionary processes in current and past selective environments [116]. Due to phenotypic plasticity [123], traits among one group of individuals could be the same or similar but greatly differ from those of another group inhabiting a different environment. The second reason is physiology. For example, snakes that have recently had ‘lunch’ will be larger and heavier than those that have not, unless the snakes with full stomachs have their stomach contents forcibly removed from their bodies before meristic measurements are taken. Physiological factors and differences are not always properly accounted for in practice because of the time constraints of field research and other nuances. The third reason is that the individuals in a population may be of the same or similar age [114]. For instance, young larval-stage individuals will be of similar size but greatly differ from mature individuals. Some reptiles tend to grow all their lives. Thus, their age determines their size [124]. The fourth reason pertains to sex, especially in the case of sexual dimorphism, particularly in terms of size [115]. Finally, the meristic characteristics of individuals can be similar due to certain environmental factors [108] or various combinations of the reasons mentioned above [125]. Research has shown that insects feeding on genetically modified plants (in this case, after modification, the plants lost the ability to send electrical signals) gain weight more rapidly than those feeding on wild-type plants, indicating that insects find it more difficult to predate plants with active systems for sending electrical signals (see [43] and the references therein). Similarly, birds that overwinter in cold climates with an abundance of food will be larger than their counterparts that travel to warmer regions.

All these examples clearly show that as with meristic variations in populations, there are other types of variations (see [126] and the references therein) that can be ascribed to distinct interlinked population structures. Consequently, variations in sex ratios [115], phenotypes [104,107], and age [108] can lead to different animal and plant [125,127,128] populations structures in terms of sex [29], phenetic [41,106], and age [8,11], respectively (PSS, PPS, PAS) (Figure 1). All the population structures mentioned thus far are specific and have different qualities, yet they could be interlinked in various ways and thus achieve a certain ‘balance’ in different species [10]. For example, in exploited populations, the disproportionate removal of older and male brown bears (Ursus arctos) via hunting causes unnatural selection, which not only can disrupt PAS and PSS but also artificially selects for smaller and less reproductively successful phenotypes (thereby disrupting the PPS) [29].

2.3.2. Population Ethological Structure

It seems that among species, not all organisms exhibit all the possible population structures; at least when comparing the same types of structures between different species (or higher taxa), ranging from highly evolved to primitive [129]. For instance, animals clearly have a population ethological structure (see [9,130] and the references therein) (PES), which could be defined as behavioral variations among individuals in a population (see [131,132,133] and the references therein), while the existence of such a structure in plants is extremely controversial (see [43,44] and the references therein). If we accept the broadened definition of a nervous system, plants might have a ‘primitive’ nervous system analogous to that of animals [43]. However, the controversial claim that plants are capable of classical Pavlovian learning, even if correct, is irrelevant because this type of learning does not constitute consciousness [44]. To date, it is still not clear what this consciousness is exactly, but it seems that there can be no ‘zone or center of consciousness’ in the brain, as consciousness results from the generalized activity of distributed cortical networks involving both gray and white matter, not a single network node in a finite time window [134].

Behavior in the animal kingdom also greatly differs among species [132,135,136] and can be grouped into at least two categories, namely, primitive and highly complex (see [133,137]), with the latter reflecting social animals with consciousness. Indeed, at first glance, behavioral diversity ranges from instincts [114] to social behaviors [9,115], with the latter only being exhibited by certain animals [131] and everything supposedly being determined by genetic factors (see [126,138] and the references therein). However, if we look deeper, then we must admit that there are also species that, in addition to instincts and social behaviors, exhibit cultural behaviors [139]. These behaviors are supposedly determined by cultural drift (see [135] and the references therein), controversial memes (see [139] and the references therein), or unknown mechanisms [137,140]. Examples of cultural behavior include the songs of birds and whales (see [141] and the references therein) or recently learned ship-attacking behaviors exhibited by certain pods of killer whales (Orcinus orca). In fact, everything regarding animal culture is even more complicated because of recent scientific findings regarding comparative thanatology. This term refers to the study of how different species perceive, react to, or understand death. It is not so clear whether thanatological behavior [142] should be ascribed to culture (or even religious-like behavior) or just instincts. Based on the literature reviewed, we can posit that there a spectrum of responses to death among animals: At one end of the spectrum are mechanistic, hard-wired, functional responses that are likely exhibited in the absence of any conscious emotional components, as exemplified by necrophoresis among social insects. At the other end of the spectrum we see complex, socially malleable patterns that are likely to incorporate emotional states including sadness and grief [129]. Whether all the behavioral diversity mentioned thus far should be ascribed to distinct parts of PES or defined as different population structures is a potential topic of discussion [68]. Discussions should not be limited to PES, as PSS can also be divided into distinct parts based on various criteria: the large diversity of reproduction systems, strategies [72,96,128], and sex determination mechanisms [120,143,144] not only among animal, plant, and fungal species, but also within each of these kingdoms.

2.3.3. Additional Population Structures?

If ecologists were to derive more population structures, it would only reveal the greater potential diversity, complexity, and uniqueness of populations of living organisms. Alternatively, even when clearly described by selected certain criteria, population structures could be grouped together. In fact, due to phenotypic plasticity, pleiotropy [145] and, most importantly, the extended, or multi-dimensional (nD), phenotype concept (see [141] and the references therein), it is quite common to see animals’ behaviors, meristic characteristics, and phenotypic variations studied indiscriminately as one ‘phenotype’ category [104,138]. Many scientists assign PAS and PSS to one group [8] and use categories based on sex and age relationships [114].

2.3.4. The Unique Role of Population Genetic Structure

Finally, now that all the necessary ecological context has been provided, we can concentrate on PGSs: the population structures (Figure 1) that alone entail genetic variations. This structure is clearly distinct; i.e., it is widely accepted that a PGS should be described as one of the major population structures. To study PGSs, certain technologies (see [32] and the references therein) and adequate funding are required. Thus, relative to the mere collection of meristic characteristics from populations during field research, it is quite complicated. In addition, collecting genetic samples can be challenging when working with endangered, invasive, or cryptic species [1]. Even so, after the abovementioned conditions are met, it is easier to correctly measure genetic variations within a population than it would be when using meristic variations [103], including with respect to variations among related non-mobile plant species [146], which are determined by the many different reasons mentioned earlier. Furthermore, organisms’ genetics determine their phenotypes [104]. Thus, a PGS is particularly interlinked with a PPS [41] and, in the case of social animals, a PES [29]. Indeed, an organism’s genetic variation partially determines its traits (i.e., genetic variation creates phenotypic variations), and the behavior of social animals can be attributed to the nD phenotype concept (see [141] and the references therein). The connection between a PGS and other population structures is also apparent. For instance, the connections between a PGS and PSS create large cycles. In mammal populations, variations in sex-specific survival rates moderate population dynamics, and the severity of these impacts likely depends on species’ social structures and mating systems [147]. Consequently, the sex of a certain individual in the next generation is determined by its genetics (PGS), which were inherited from previous generations [143]. In other words, genetics determine the sex of an individual, and vice versa. Please note that this clear cycle applies to many but not all animal species, as there are species in which sex is mostly determined environmentally [148], such as in the case of temperature differences during the incubation of eggs [149]. In conclusion, a PGS must be treated as a structure essential to the populations of all living species, as all living species have genetic diversity.

3. What?

To understand what a PGS is, we need to understand the genetic diversity of a species. There are many reviews dedicated to intraspecific genetic diversity (see [14,21,72]), its different aspects [3,150,151], and how to study it [7] with molecular markers (see [152,153] and the references therein). Thus, interested readers are referred to the relevant literature sources. In this review, we define genetic diversity as DNA variations found in organisms. This definition has some disadvantages.

First, it is oversimplified, as some other biological molecules are known to constitute genetic material. For instance, viruses are considered quasispecies (see [154]) and not included in what is considered life, yet they are still biological–genetic systems and, in some viruses, RNA is the essential genetic material (see [73,155] and the references therein). Moreover, some proteins, such as prions [156], serve as hereditary factors. These particular examples are outside the scope of this review. However, on a broader scale, genetic diversity includes all heritable variations at the molecular level.

Second, since all species are genetically distinct, this definition encompasses both interspecific and intraspecific genetic diversity. Consequently, intraspecific genetic diversity could be defined as DNA variations found within a species. To sum up, DNA variations can and should be treated as the key to understanding intraspecific genetic diversity, necessitating the consideration of DNA and its variations in more detail.

3.1. DNA, Its Variations, and Genetic Diversity

Theoretically, the last individual of a species would represent all the existing variations in the DNA sequences of its kind, and its DNA would be equal to this organism’s genome and its species’ genetic diversity. As we will see in the following paragraphs, everything is much more complicated at a practical level, starting with DNA, moving on to its variations, and ending with genomes, pangenomes [157], and additional uncertainties and questions regarding intraspecific genetic diversity.

3.1.1. DNA Diversity and Terminology

The commonly used abbreviation DNA gives us limited information, as it only indicates that this is a macromolecule of nucleic acid containing deoxyribose. Additional information can be obtained from various criteria and context. For instance, if DNA is extracted from ancient material, such as bones from specimens of animals dated to have lived centuries ago, during the Ice Age (see [158,159,160] and the references therein) or from even farther back on the evolutionary timescales, or has been obtained from the environment, it is called aDNA or eDNA (see [1] and the references therein), respectively. There are two or more distinct genomes within eukaryote cells (see [161] and the references therein), which are multicellular life forms. Thus, based on the DNA belonging to these genomes, different terms are applied: DNA is called nDNA [162] or nuDNA if it corresponds to a nuclear genome; mtDNA if it corresponds to a mitochondrial genome (mitogenome), which is found in mitochondria in the cell [163]; and cpDNA [146] if it corresponds to a chloroplast genome, which is absent in animals and present in chloroplasts in plants as well as in algae or cyanobacteria [164]. Besides nuclear, mitochondrial, and chloroplast genomes, other types include the apicoplast genome (in Apicomplexa), the kinetoplast genome (in kinetoplastid protists), nucleomorph genomes (in some algae), plasmid genomes (in prokaryotes and some eukaryotes), viral genomes, and genomes of endosymbionts. Typically, in various organisms already known to science, genomic DNA can be either single-stranded (ssDNA) [165] or double-stranded (dsDNA) (most eukaryotes), and only certain parts of the genome can have DNA containing three strands [166], such as mtDNA D-loops [167], or even more [168] strands. It has also already been revealed that the complexity and variety of DNA forms are not limited to different numbers of strands, yet all of them are formed from nucleotides (A, G, C, and T) (see [169] and the references therein).

3.1.2. Variations Within DNA Sequences

In general, all DNA variations, including epigenetic modifications of nucleotides, can be reduced to and understood as all possible variants of nucleotide positions within an ssDNA sequence and observed by aligning and comparing two or more sequences. Because some aligned sequences, even from different specimens from the same species population, can be longer or shorter in addition to having differences in the positioning of the four possible (A, G, C, and T) nucleotides, during analysis, a fifth possible position appears, which indicates an indel (insertion or deletion) and is marked as a gap (-). Indels, especially those that represent one or a few nucleotide deletions or insertions, are quite often still ignored in DNA sequence analysis when quantitative genetic parameters, such as haplotype diversity (H_d) [170] and nucleotide diversity (π) [171], are calculated. That is not to say that the mentioned parameters cannot be calculated, both when including gaps as a fifth nucleotide position in DNA and when excluding them. Evidence that indels could provide an additional layer of important information, and thus, should not be discarded, keeps growing [172,173].

3.1.3. Modern Approaches Used to Reveal and Research Variations Within DNA Sequences

While different methods and molecular DNA markers reveal various DNA variations within organisms [152], only sequencing [92] allows us to study each nucleotide position in the short and long DNA sequences obtained [174]. That is, less successful sequencing results (some positions in the DNA can be marked as N and indicate all four of the possible nucleotides, i.e., maximum uncertainty, or marked with other letters, indicating that in certain positions, one or two particular nucleotides might not be present) and other different methods provide quite reliable yet more abstract, ambiguous, or even unclear data based on their methodological nuances. For instance, DNA sequencing results that provide less accurate data could be used for certain studies, but their potential for use in the future is much lower than that of successful sequencing results, which ideally represent each nucleotide within a DNA strand and generate the most useful data for researchers. Typically, DNA microsatellite research only generates information about differences in DNA length (see [172]) arising from variable number tandem repeats (VNTRs) among individuals [175,176]. The major principle is as follows: if one individual in a certain locus has a low number of tandem repeats, like (AC)₂, and another individual at the same locus has a larger number of tandem repeats, like (AC)₁₀, then this length difference could be easily revealed via gel electrophoresis. Please note that during this DNA fingerprinting [177] technique, expected tandem repeats such as (AC)₁₀ in the locus of a certain individual could differ by one or more nucleotides, which would not be revealed without additional DNA sequencing. Allozymes (see [72] and the references therein) likely constitute the most indirect and abstract way of acquiring information about DNA sequence variation. At both technological and economical levels, immense progress in direct DNA sequencing has been achieved within just a few decades (see [161] and the references therein). The development and features of sequencing technology from 1953 to 2023 have been presented in [178]. In short, the high cost and low throughput associated with First-Generation Sequencing (FGS), i.e., Sanger sequencing, which has high accuracy and is still used even today at smaller scales, led to its widespread replacement by technologies based on massively parallel sequencing and, later, Third-Generation Sequencing (TGS)—which enables sequencing of individual molecules—owing to specific problems that this form of sequencing addressed (see [179] and the references therein). Basically, modern Next-Generation Sequencing (NGS) assortments for researchers are rapidly increasing (see [28] and the references therein); however, whole-genome sequencing (WGS) of eukaryotes remains challenging [180], and scientists still need to operate on an ‘almost whole-genome sequencing’ basis (see [174,181] and the references therein). Consequently, a small percentage of DNA variations in eukaryotes remained hidden at the beginning of the 21st century.

3.1.4. Problematics of the Interpretation of the Meaning of DNA Variations

Despite the successful generation of clear data on studied organisms obtained via DNA sequencing, constituting only one of the great achievements in this regard, there are also major challenges (see [161] and the references therein). These challenges are both technical, such as the saving of the information obtained in databases (see [92,182] and the references therein) and annotation [174,183], and scientific, such as the genetic–biological interpretation of the DNA sequences obtained [181]. DNA consists of only A, G, C, and T and their various combinations within a sequence, but not all possible combinations are currently treated as meaningful when scientists cannot detect any associated biological function or effect. Consequently, it is possible to use only four or five distinct characters to represent all DNA variations, yet it is not wise to totally ignore higher-level organizations of structural DNA variations, such as unique sequences, alleles, genes, and pseudogenes (see [163] and the references therein). Indeed, there are both variable [92] and conservative parts in DNA (see [184] and the references therein). Thus, it is reasonable and practical to use this information as an additional level of DNA variation reflecting certain patterns of evolutionary history [180] within species (see [185]) and among distinct species or even in comparisons of more diverse taxonomically distinct groups of organisms [172,186]. This feature of DNA is also very useful for the creation or selection of molecular markers which are suitable for research into particular scientific questions, especially those within population genetics and evolutionary biology frameworks. In addition, it is also crucial for the genetic classification and identification [187] of different species via DNA-barcoding (see [188] and the references therein) applications. In particular, DNA fingerprinting [189], like biparental DNA microsatellites, enables us to obtain individuals’ genetic profiles, while DNA barcoding, using more conservative parts of DNA together with variable ones, can be used to obtain distinct species profiles [190,191].

Many decades ago, population geneticists proposed that most parts of DNA are selectively neutral (see [72] and the references therein); at the same time, the scientific consensus that only the most meaningful DNA sequences encode proteins (see [192] and the references therein), sequences called genes, was still quite strong (see [92] and the references therein). Typically, selective neutrality means that the conservative parts of DNA are affected by natural selection, while variable parts have minimal effect or are not affected at all by this evolutionary force (see [193] and the references therein). Both substitutions in genes and selectively neutral genetic variations [180], as well as adjacent DNA regions, are included in the concept of genetic diversity. This applies not only to nuDNA, but also mtDNA and cpDNA. Consequently, before the results of the first WGS of the human species were obtained, it was expected that many more genes than what was eventually recovered would be identified (see [194] and the references therein), which was soon after indirectly confirmed by the sequencing of the nuclear genomes of the selected model animal species [195,196]. These empirical data on a relatively low number of genes from humans and other species (see [28] and the references therein) caused a paradigm shift (see [197] and the references therein): it was realized that not only structural but also regulatory parts of DNA become increasingly complicated in the genomes of evolutionary sophisticated life forms [198]. Indeed, previously, most parts of DNA—and, in turn, sequences, especially repeating ones like CpG islands and those that do not encode proteins—were called ‘junk DNA’ (see [199] and the references therein), but we now have increasing evidence that this presupposed idea and the corresponding term do not reflect the biological function of the DNA. In addition to single-nucleotide polymorphisms (SNPs) and indels, genomic variation includes many long-fragment structural variants (SVs), such as copy number variations (CNVs), rearrangements, and presence/absence variants (PAVs); most importantly, despite representing only 0.2% of the types of genomic variation, SVs can still affect 4–12% of coding genes by changing gene dosage levels and interfering with gene function in humans (see [178] and the references therein). Genomic repetitive DNA sequences (REPs), including transposable elements (TEs) and satellite DNA (satDNA), typically evolve much faster than single-copy DNA sequences and are widespread in eukaryotes, influencing biological form and function (see [183] and the references therein). That is, ‘junk DNA’ adopts more than a dozen alternatives to B-DNA structures, such as self-annealed hairpins, Z-DNA, three-stranded triplexes (H-DNA), and four-stranded guanine quadruplex structures (G4 DNA), and these dynamic conformations can act as functional genomic elements involved in DNA replication and transcription, chromatin organization, and genome stability [169].

3.1.5. From DNA Sequence Variations to Genomes

A genome sequence is a snapshot of an individual (in the case of procaryotes and certain parasitic eucaryotes, a strain) at a given point in time [157]. By combining broad-scale genome-sequencing results with complementary information from transcriptomics and gene expression, it is possible to describe, compare, and even classify genomes [183]. A reference genome is a standardized DNA sequence representing the ‘typical’ genome of a species rather than the complete DNA sequence of an individual, whereas genomic variation refers to a variety of changes that occur in a DNA sequence that can significantly affect the phenotype and fitness of an organism [28]. A growing number of reference genomes are allowing us to employ comparative genomics, reveal previously hidden things, and update our understanding of the functions of DNA (see [174] and the references therein). Consequently, the modern situation is drastically changing into precautionary approaches regarding the possible functions of DNA sequences [200], as it has already been revealed that there are genes that do not encode proteins (see [192] and the references therein); some genes are more important [178,180] than others for organisms’ functions [201] and survival; and more attention has been dedicated to REPs, regulatory elements [202], and mechanisms, and unique DNA sequences with unclear functions (see [92] and the references therein). It is now general knowledge that only a small part of all the DNA of an organism consists of protein-coding genes (see [203] and the references therein). For instance, based on the method selected, the estimated number of protein-coding genes in the Eurasian perch (Perca fluviatilis) ranges from 23,397 to 24,326, yet the total scaffold size (bp) ranges from 630,662,671 to 958,225,764 bp (see [204] and the references therein). Similarly, most of the human nuclear genome is made up of non-coding sequences like introns (almost 26%) and TEs (nearly 45%), and only less than 1.5% of it consists of the suspected 20,000–25,000 protein-coding sequences [205]. The nuclear genome sizes of selected representative species from several major different taxonomic groups of organisms have been presented in a recent review (see [28] and the references therein).

The potential of comparative genomics has been reduced by unequal research and representation of the genomes of different organisms encompassing distinct evolutionary and taxonomic groups. Over 50% of animal genomes belong to the phylum Chordata, even though chordates account for just 3.9% of all animal species, whereas assemblies of Spiralia (a monophyletic clade encompassing worms, mollusks, etc.) represent 4.8% of available animal genomes, even though spiralians make up more than one-third of known marine animals and play crucial roles in marine ecosystems (see [180] and the references therein). In general, animal nuDNA can have up to billions of base pairs (bp) or gigabases, is diploid, is inherited from both parents, and typically contains tens of thousands of genes; whereas mtDNA is circular, about 16,000 bp long, contains 37 genes, is haploid, and is maternally inherited [204].

The emergence and advancement of TGS technologies have markedly improved the decoding of highly repetitive regions such as centromeres and telomeres in plant nuclear genomes, and a nearly complete assembly of polyploid Arabidopsis arenosa was achieved (although the genome remains fragmented due to its high allelic similarity) in 2021 (see [179] and the references therein). In plants, mitogenomes are characterized by significant variability in size (ranging from 109 kb to over 10 Mb) and structural complexity and central to energy production, while chloroplast genomes are essential for photosynthesis and other biosynthetic activities (see [161] and the references therein). Most chloroplast proteins are encoded by the nucleus, but the chloroplast genomes still encode between 50 and 200 essential proteins depending on the plant species. cpDNA differs between the plant species both in terms of the size (ranging from 15,553 to 521,168 bp) and form (multi-branched linear or circular structures) they may take, and examples of comparisons of the general characteristics of different three genomes of the same plant species are already available in the scientific literature (see [164] and the references therein).

3.1.6. From Genomes to Pangenomes

In the last few decades, genomics has proven to be fundamental in the study of vertebrate genome evolution [181] and expanded to far more than just comparisons of the genomes of different species, as combining genomics with population genetics allowed scientists to create and establish population genomics (see [92,206] and the references therein), which has greatly benefitted studies and comparisons of genomes within an intraspecific genetic–genomic diversity context. The key realization in this regard is that a single reference genome pattern cannot represent genetic diversity at the species level [178]. Consequently, population genomics currently operates based on the crucial but still debated concept of a pangenome, which is defined as the set of all genes present in a given species and can be subdivided into the accessory genome, present in only some genomes, and the core genome, present in all genomes, and is applied mostly at the intraspecific level but can also be used for other taxonomic units (see [157] and the references therein). In fact, this concept was first created for prokaryotes, but it has since been expanded to eukaryotes and even viruses [178]. New theoretical, comparative, and experimental approaches have already been employed to understand how and why pangenome dynamics vary over space and time despite greater sampling and sequencing expansion of the catalog of the contents of pangenomes [157]. Even so, the maturity of multi-omics is expected to further promote the development of pangenomics, with many practical applications in the near future [178].

3.1.7. From the DNA Level to the Chromosome Level

Finally, the concept of genetic diversity clearly encompasses organisms’ different levels of organization of chromosomes and their genetic variability. The lack of coordination between genome assemblies and previous cytogenetic results has led to a lack of information about genome organization and evolution, and it may also generate misunderstandings among researchers. Thus, bridging the gap between genomic and cytogenetic data is the main aim of chromosomics [181]; that is, the nuclear genome can be understood as distinct genetic parts within distinct chromosomes, yet it can still be reduced to a long DNA sequence, whereas the organization levels of chromosomes require a broader understanding, specifically with respect to DNA and protein complexes in space and time. Indeed, understanding the molecular mechanisms driving the three-dimensional (3D) organization of a genome is a major challenge for the current and next generations of scientists. To ensure optimal functionality and stability of the genome, the elements of DNA controlled by various protein complexes and epigenetic modifications that together establish the 3D organization of the genome, which facilitates an efficient regulation of the genome, including interactions between distant DNA elements [207]. In this paper, we limit our scope as much as possible to DNA variability within a chromosome context. More information regarding chromosomes, karyotypes, proteomics, transcriptomics, and cell cycles can be found in other researchers’ studies (see [92,174,181] and the references therein).

Aneuploidy (see [208]) is the simplest system we can use to research genetic diversity at the chromosome level, as alleles can be detected only in certain loci of chromosomes and directly translate to traits revealed in phenotypes. The situation that occurs when alleles are deleterious, defined by Gargiulo et al. [93], is called realized load—part of a broader concept known as genetic load, which denotes genetic variation that reduces the fitness of a population (in comparison with a reference genotype with maximum fitness). However, diploids and polyploids, other life forms on Earth, create additional qualitative and quantitative patterns. Polyploids can be categorized into two types based on their formation mechanisms: autopolyploids, which arise from whole-genome duplication (WGD) within a single species, and allopolyploids, which result from hybridization between different species, followed by genome doubling/multiplication, incorporating genetic material from at least two ancestral species (see [179] and the references therein). Alleles of the same locus in nuDNA can be detected in two qualitative positions in chromosomes of diploid organisms. This creates genotypes (see [86] and the references therein) that are either homozygotes or heterozygotes. It is often the case that one allele is dominant and another is recessive. Homozygotes of recessive alleles could lead to clear expression of phenotypes that under common conditions have a weakened ability to adapt, survive, or reproduce. Heterozygotes can have a masking effect on phenotypes. As with realized load, this phenomenon has also been defined, but with another term: masked load (see [93] (and the references therein). Heterozygotes enable us to evaluate heterozygosity, which is a measure of genetic diversity: specifically, it is the probability that two randomly sampled gene copies in a population carry distinct alleles [72]. We can also use alternative genetic metrics that respond more quickly to abundance declines than heterozygosity or gene diversity, such as allelic richness or long runs of homozygosity, which can detect inbreeding before widespread losses of genetic diversity [151]. It is unlikely for individual heterozygosity to be determined using eDNA, as eDNA often contains fragmented DNA that cannot be assigned to a specific cell [1]. In general, both higher heterozygosity and a slower loss of heterozygosity compared with diploids are characteristics of autopolyploids [93]. In addition to nuDNA, eukaryotes have mtDNA, which is treated as a single chromosome. Alleles found in mtDNA are ascribed as haplotypes [38], and the same naming rule applies to chloroplasts [209] and some regions of nuDNA, such as Y chromosome genetic regions [210].

3.1.8. Crucial Open Questions Regarding Genetic Diversity

Critically, within a eukaryotic cell, there is not one mtDNA copy but many copies, and they can differ according to their DNA sequences. In addition, at least among animal species, copies of mtDNA from two or more distinct species merged via hybridization can be found [211]. There is a similar situation with respect to cpDNA and chloroplasts within plants: on average, plant cells contain anywhere from 1000 to 1700 copies of chloroplast nucleoids [164]. Certain additional chromosomes or parts of them can be found in the karyotypes of some individuals from a given population (see [212] and the references therein) as well. The complications do not end here, as many eukaryotes have many cells [5] and despite the assumption that these cells are genetically identical, it is only generally accepted scientific oversimplification. The pangenome concept only partially solves these problems. Pangenomes arise due to gene gain via genomes from other species through horizontal gene transfer (HGT) and differential gene loss among genomes, and they have been described in both prokaryotes and eukaryotes. Yet, our current view of pangenome variation is incomplete [157]. In addition, this concept only concerns genes, not all DNA variants. Should somatic cells that exhibit differences in DNA corresponding to at least one nucleotide position compared with other cells from the same organism—which are presumably lost once the organism dies, as only generative cells are transferred to the next generation—be included in the concept of genetic diversity? If so, should this apply to cancer cells as well? Should somatic cells that are no longer within an organism but instead exist in the environment, constituting forms of eDNA (see [1] and the references therein), be included in genetic diversity or not, as they no longer belong to the individual and, in turn, are no longer included in the population of living things?

3.2. Intraspecific Genetic Diversity Within the Context of Microevolution

3.2.1. Genetic Diversity, Adaptation, Survival, and Evolutionary Potential

Any biotic or abiotic change in a population’s environment that can negatively affect its survival and reproduction is defined as a disturbance event [93]. The first biological response to this disturbance event exhibited by the individuals within this population is short-term acclimatization. An organism’s acclimatization potential can be defined as its ability to modify a phenotype in response to environmental changes without altering the corresponding genotype [213]. In contrast, genetic diversity entails evolutionary potential (EP) and is created and affected by evolutionary forces [214]. In the case of intraspecific genetic diversity, we observe genotype alterations at smaller or larger scales, yet a temporal disconnects between a change in the environment and the genetic change required to maintain or recover fitness, known as adaptational lag (see [93] and the references therein), can occur.

EP, together with dispersal and colonization and phenotypic plasticity, is the main component of the adaptive capacity of a species, and it is defined as the capacity to evolve genetically based changes in traits that increase fitness under changing conditions. Although it is difficult to quantify and evaluate for extinction risk assessments, disregarding EP can quickly lead to ineffective allocation of resources and inadequate recovery planning (see [94] and the references therein). This concept should be understood as a broader term than adaptive potential. First, in theory, environmentally responsive epigenetic mechanisms can allow for acclimatization and adaptive phenotypes to arise faster than DNA sequence-based mechanisms alone. Second, it has already been practically demonstrated that phenotypic expression can be modulated by factors beyond the coding DNA across a variety of traits and species (see [213] and the references therein). Third, the microbiome extends host EP [215]. According to Gargiulo et al. [93], adaptive potential is the genetic variation needed to respond to selection, and this term includes functional as well as neutral and nearly neutral genetic variation that might become adaptive under changing environmental conditions. It should be mentioned that there is ongoing debate about whether neutral genetic diversity can be truly representative of adaptive potential, as the genes detected do not have any direct effect on population fitness; rather, in general, the reduction in genetic diversity can cause reduced phenotypic variability, which, in turn, may affect population viability and stability (see [3] and the references therein). Despite the problems associated with EP evaluation, the general rule of the thumb is that species with great genetic diversity, especially if it is linked with species-wide geographical distribution, have much greater EP than species with low genetic diversity, which is typically also indicated by a low N_e. One way or another, we need to be aware that extinction debt, i.e., a delay between a disturbance event that leads to the local extinction of a species and the actual moment of extinction [93], has not already occurred in this situation.

3.2.2. Intraspecific Genetic Diversity and Evolutionary Forces

Mueller et al. [42] explained that evolutionary biology is concerned with transgenerational change and indicated that the prevailing evolutionary theory conceptualizes the underlying process as an interplay between five central parameters acting on genetic variation: mutations of the DNA backbone generate genetic variation, which is depleted by random genetic drift, reorganized by recombination, and redistributed by gene flow and the filtering of phenotypes via natural selection. However, it is not clear whether these scientists are referring to the five central parameters as being synonymous with evolutionary forces. Traditionally, most scientific studies, especially old ones, from population genetics ascribe only four of them to evolutionary forces (see [216] and the references therein), excluding recombination.

The first evolutionary force creates new evolutionary material (see [73] and the references therein]) at the individual, population [72], and species levels; it is most often called mutation. The more correct term would probably be mutability or mutagenesis, which defines the process of the appearance of mutations. In short, this process is mostly random, yet mutagens (both certain chemicals and physical phenomena like radiation) can induce mutagenesis. Any nucleotide change in DNA relative to an ancestral or reference sequence is considered a mutation. There are many different types of mutations (based on DNA changes) and, in turn, protein or even chromosome modifications; those that have effects on an organism’s functioning and survival are called lethal mutations (see [92,145,217,218,219] and the references therein). The rate of mutation is not constant across the genome and among different species; this fact explains part of the observed variation in genetic diversity (see [72] and the references therein). Genomic regions with higher mutation rates such as microsatellites (for which the average heterozygosity typically ranges from 0.6 to 0.9) will exhibit higher indices of genetic diversity than regions usually found in two allelic states (with a maximum expected heterozygosity equal to 0.5), such as SNPs [93]. Neutral models in population genetics assume that mutations at different sites in the genome are not linked, and this is quite justifiable but questionable within the context of the assumption of pangenomes in eukaryotic species that engage in obligatory sexual reproduction [157]. The nonrandom association of alleles at different loci is called linkage disequilibrium (LD) [85]. More detailed information about this evolutionary force can be found in previous scientific work (see [86,92,219] and the references therein).

The second force is gene drift (or random genetic drift), defined as the random sampling of allelic variants that may lead to changes in the frequency of existing alleles from one generation to the next due to chance [85]. This evolutionary force randomly fixates or eliminates alleles and causes populations to genetically differentiate, especially when these populations have a small N_e (see [72] and the references therein). Lengthening of the juvenile life stage in animals and the mean seed dormancy in plants increases N_e, and autopolyploid species lose genetic variation via drift more slowly than diploid species not only because of a larger N_e but also because of a greater number of orthologous alleles (see [93] and the references therein). See Moya et al. [73], Angst et al. [220], and Gerstein & Sharp [221] for more detailed information regarding gene drift.

The third force is associated with organisms’ travels, called migrations, and this force is called gene flow [7]. For example, individuals from population A could migrate and reach population B, but unless these individuals reproduce and have offspring, this process is not considered gene flow. Usually, for the representation of unrestricted and restricted gene flow, scientists use the concept of panmixia [96] and the term isolation by distance (IBD), which is defined as the decrease in the genetic similarity among individuals or populations as the geographic distance between them increases [85]. Not only geographical distance but also contamination can act as barriers to gene flow [31]. Typically, such cases are described using the term isolation by barrier (IBB) [222]. Conclusions regarding the strength and consistency of isolation by time (IBT), which is not exactly equivalent to IBD (owing to differences between dispersal in space and dispersal in time), in nature require more studies specifically designed to test for temporal restrictions on gene flow, yet the existence of this phenomenon is supported by previous evidence (see [223] and the references therein). In general, gene flow can serve to either reduce EP by swamping out locally adaptive variants or increase it by introducing beneficial adaptive variants (see [94] and the references therein). Gene flow is a fundamental evolutionary process involving the movement of genes between populations through the dispersal and successful reproduction of individuals, gametes, or propagules, and it contributes to genetic homogenization among populations; yet, when restricted, it allows for genetic divergence [224]. In the scientific literature, gene flow is quite often hidden behind the term population connectivity [225] and involves various barrier investigations. As a result of scientists’ attempts to study gene flow in more comprehensive and realistic ways within the context of environmental heterogeneity, Landscape genetics (LG) (see [75] and the references therein) was born, and quite recently new approaches have emerged from this field: Seascape genetics (SG) (see [24] and the references therein) and River genetics (RG) (see [222] and the references therein). A prognosis of the future of gene flow investigations within the context of LG and SG can be made. On the one hand, it is likely that, over time, they will be divided into smaller scientific research areas based on types of environments that are found in nature, such as estuary or lake genetics. However, on the other hand, they could also achieve synthesis in such a way that large, new research areas based on main biogeographic regions will emerge: Afrotropical, Australasian, Nearctic, Neotropical, Indo-Malayan, West Palearctic, and East Palearctic [2] genetics. It should be noted that both scenarios could occur, as the realization of one scenario does not negate the other.

Finally, the fourth evolutionary force is called natural selection. Although this phenomenon was noticed and defined prior to Charles Darwin’s famous work, it was popularized by this father of the theory of biological evolution, and our current understanding of this force developed because of later works in population genetics (see [72] and the references therein). Though selection operates on individual phenotypes, its population-level consequence is a change in allele frequencies (or other genetic variants) over generations, a core principle in population genetics (see [226] and the references therein). Adaptive genetic responses to selection can take form within a few generations and involve, for most traits, small allele frequency shifts at many partially redundant loci, and they are most effective in large populations, while environmental heterogeneity maintains more suitable habitats for individual survival after a disturbance (see [93] and the references therein) and leads to microevolution in the long-term. Selection can also vary through the reproductive season; in such cases, we expect adaptive divergence between groups that reproduce at different times: when IBT is the prominent force, variation in selection may lead to adaptation by time (ABT); that is, the formation of adaptive temporal variation in phenotypic traits (see [223] and the references therein). Both selective sweeps (the replacement of all alleles in a population by a selected allele) and drift (the random loss of lineages from a population by sampling each generation) can cause lineages to become extinct [227]. It can be concluded that linked selection plays an important part both in overall intraspecific genetic diversity and in the variation in diversity within a genome, and it seems that polymorphism could be predictable based on the life history of a species [72].

In more recent studies, recombination has also been described to be a fifth evolutionary force [73]. On the one hand, this is the correct course of action, as this process, in essence, differs from the other four evolutionary forces; on the other hand, it complicates things because even one change in a nucleotide in a certain position in DNA is typically defined as a mutation (recombination also changes DNA nucleotides). Finally, Adams et al. [1] state that with further optimization, the emergent field of eDNA holds great potential as part of the population genetics toolkit: currently, significant sequencing, bioinformatic, and statistical challenges still need to be overcome to transcend proof-of-concept studies in order to answer questions about gene flow, genetic drift, mutation, and natural selection. Other phenomena can also affect genetic diversity in various ways (see [75,92], and the references therein), but they do not have the status of the previously mentioned forces. For more information, see [228,229].

3.3. From Intraspecific Genetic Diversity to Population Genetic Structure

Since its origin in the 1980s, the concept and use of the term biodiversity have evolved quickly and now have multiple dimensions (nD), encompassing diverse values; i.e., different people attribute different meanings and levels of importance to it. Thus, many scientists agree that the scale of genetic diversity (despite including domesticated diversity, which is far from being insignificant) is very small compared with the scale of biodiversity on Earth but that it still has immense biological–genetic value (see [5] and the references therein) that should not be reduced to only financial costs and gain. Moreover, genetic diversity also can be defined as being at least two-dimensional (2D), possessing two distinct major interspecific and intraspecific levels. In the following paragraphs, we will try to answer a critical question within the PGS context: could even intraspecific genetic diversity be defined as having nD?

3.3.1. Toward a Greater Understanding of the Population Genetic Structure of a Species

At a practical level, intraspecific genetic diversity can be understood as the result of cumulative environmental and geological processes that have occurred at varying temporal and spatial scales, each leaving interpretable marks in a genome [222]. Intraspecific genetic diversity is essential for maintaining healthy populations and ecosystems [21]. Overfishing drives population declines which, in turn, drive the loss of intraspecific genetic diversity. Many studies provide evidence of declines in genetic diversity, yet controversy still exists within the literature, as some studies show evidence that there have been no changes in genetic diversity despite decades of overharvesting. Thus, the apparent discrepancy in the literature should be examined to understand what biological and ecological processes are driving the differences in results (see [3] and the references therein). Species that have undergone particularly significant declines in abundance or range and species with historically low abundance or small ranges are all expected to have low intraspecific genetic diversity [151]. Detecting a recent decrease in genetic diversity in tree populations is difficult, as remnant trees will reflect the genetic diversity of the previous generation, as expected in species with traits favoring time lags [93].

From a theoretical viewpoint, intraspecific genetic diversity can be thought of as reflecting the balance between the appearance and disappearance of genetic variants [72], whereas the pattern of the distribution of genetic variation within and between populations is referred to as the PGS of the species [7]. For example, studies on the population genetics of Australian white sharks have demonstrated inconsistency in their PGS across the species’ continental range [32], meaning that researchers studied not just DNA variations, i.e., intraspecific genetic diversity, within the species but also their combined patterns within and among studied samples dependent on geographical locations that represent at least one real population. Schematic representations of this definition of a PGS can be found in Figure 2 and Figure 3. The concept and definition of species employed are crucial for a PGS, as, one way or another, we must operate at both the species level and the population level. Notably, even panmictic populations of presupposed panmictic species still exhibit patterns of genetic diversity and, in turn, have a PGS (see [7] and the references therein) that is usually described as ‘limited’, ‘weak,’ or even having ‘no structure’. These definition-like words can be contrasted with the cases where a PGS is determined among two or more populations, as then different words are used: ‘strong’, ‘hierarchical’, stable [36], etc. Just as it is currently impossible to study all individuals in a species due to technological limitations (because of living systems’ biological–ecological complexity in space and time), scientists can only expect to acquire enough data on studied species genetics and, after analysis, acquire a picture of a hypothetical PGS that effectively represents the real PGS. Because of this, different sampling strategies among studies [1]; selected techniques, including genetic markers [152]; statistical tools [93]; and interpretations by researchers could yield distinct or even conflicting and controversial results, revelations, and elaborations (see [3] and the references therein). This applies both to selectively neutral DNA research and that are affected by natural selection and, in turn, research using genetic markers. Some genetic markers are more common and useful than others, yet all information obtained about PGSs is important and thus should not be discarded (barring cases of crucial errors or fraud), and it gives us snapshots about real phenomena, at least the ones that existed during the time of research. Research on genetic diversity patterns among populations conducted using, for example, the random amplified DNA (RAPD) technique (see [152] and the references therein) is still valid, despite increased technological concerns compared with SNP [3], and could reveal important information that, theoretically, could be overlooked when using other types of genetic markers. From a scientific perspective, at the methodological level, population genetics should ideally be equal to or surpass population genomics and use all possible DNA information from the genomes of individuals. However, at the moment, this is unrealistic; even if this ideal were to be realized, there would still be rationale to use shorter DNA fragments for certain types of research within population genetics. Consequently, certain species’ pangenomes, defined as the set of all genes found within a species, can and should be considered part of its PGS. By this logic, other genetic material that does not include genes from a pangenome could be less selectively important, and it would be reasonable for scientists to define it as independent genetic information within species. This naturally existing part within each species can also be divided into smaller parts using the major parts of the pangenome, i.e., core and accessory genomes, and open and closed genomes (see [157]). Gong et al.’s [178] definition of a pangenome as a collection of all nonredundant DNA sequences in a species or population, instead of just all the genes, lacks clarity. Indeed, if components other than just genes are included in the concept of a pangenome, it will interfere with the term of a PGS, as it should encompass all DNA variants, including pangenomes. The same applies to the definition of a gene, as it is central to the clear definition of the concept of a pangenome, raising questions like ‘does this only include all genes that encode proteins, or is RNA included?’ and ‘are other nearby gene sequences or spacers within genes included?’.

3.3.2. Problems with Non-Standardized Definitions and a Possible Solution

Sul et al. [26] suggested another definition for a PGS: any form of relatedness in a sample, including ancestry differences or cryptic relatedness. When faced with multiple geographical sites, organism cohorts based on age differences or arrival at a specific location, or even samples representing an ancestral population in comparison to a contemporary one, F-statistics—especially the fixation index (F_ST), which is a crucial measure of a PGS for estimating population differentiation (see [222] and the references therein)—can be used to infer various aspects of PGSs [85]. While the descriptions of PGSs in the literature are not standardized in general, it is worth mentioning the following preliminary definitions. A limited PGS means very little genetic differentiation between populations. A weak PGS refers to low differentiation, where there is some gene flow or little genetic variation. A strong PGS is characterized by high genetic differentiation, often resulting from physical barriers or limited gene flow. A cryptic PGS describes cases where a PGS exists but is not evident from morphological or ecological data. A stable PGS means that the observed genetic patterns remain stable over time. A hierarchical PGS involves multiple layers of genetic differentiation, such as subpopulations located in larger regions. A mosaic PGS refers to a patchy or irregular pattern of genetic variation that does not correspond to geographical or physical barriers. A native PGS refers to the genetic patterns found in populations located in natural, unintroduced areas. A genomic PGS is based on whole-genome data, allowing the detection of subtle genetic differences that may not be apparent when using other genetic markers. In this perspective review, we use the first definition as the basis for theoretical considerations as it has already been validated though a scientific consensus and, in our opinion, is the most appropriate.

3.3.3. Population Genetic Structure as a Dimensional Genetic Mosaic

Thus far, neither physicists (see [134] and the references therein) nor biologists or geneticists [14,72] have been able to avoid the word ‘relatively’ when describing their research [230]; we will also continue this tradition, as a better understanding of PGSs is directly linked to relativity. For instance, the meaning of low genetic diversity is relative, at least in some contexts (see [151]), and F_ST reflects the proportion of allelic variation contained in subpopulations relative to the total genetic variation (see [222] and the references therein). Since processes in nature, especially in populations of living organisms, are stochastic [231,232] and dynamic [233,234] yet relatively static [18], the same rules apply to the PGSs of species, whose representatives are distributed in particular geographic territories at a particular time. Consequently, just like electrons in atoms are always moving and still create relatively stable building blocks under given conditions and environments, we can describe a PGS within species as indeed existing as a relatively stable, temporal, 3D (in terms of spatiality and elevation) structure (see [24,223] and the references therein). In other words, in essence, this 4D (3D with time as a distinct dimension) structure itself is quite a fragile genetic mosaic, which has been confirmed in terms of determined IBD [85] and IBT [235] patterns in different species. In addition, most LG, SG, and RG analyses seek to use genetic data to test hypotheses about IBB, such as roads and the influence of landscapes, seascapes, and riverscapes on gene flow: these approaches move beyond explaining genetic structure solely as a function of IBD by generating models that describe how specific habitats enhance or provide resistance to the movement of individuals and testing whether these models explain genetic differences better than IBD or panmixia (see [222] and the references therein). Consequently, many studies which are considered as examples of LG, SG, and RG approaches support our previously mentioned view regarding PGS dimensions. This is not surprising as many, if not most, biological systems are created from different levels of mosaics. Forests are mosaics of different trees, smaller plants, and fungal species (see [236] and the references therein). Some animal species, such as four echidna species (Tachyglossidae) [144], the platypus Ornithorhynchus anatinus [2], and the endangered okapi Okapia johnstoni [234], look or even function [237] like mosaic combinations (chimeras) of different animals [238,239]. In the same organisms, cells, especially cancer cells [136], can also be morphological and genetic mosaics (see [240]). Finally, the human brain is a kind of mosaic in which neurons are grouped together to form functional circuits, processing information hierarchically in the visual cortex [134].

3.3.4. Population Genetic Structure and Ethology

Keeping in mind the information presented above, there is little doubt that a PGS exists as a 4D phenomenon and should be treated as such. However, it has been known for some time that migratory behaviors in birds are strongly genetically controlled and can evolve over surprisingly short evolutionary timescales: many species inherit spatio-temporal migratory programs, allowing even juveniles to follow precise migratory routes without prior experience, and such behaviors have been observed to shift significantly within as little as 25 years (see [241] and the references therein). Research on genetics associated with human and animal behaviors started with research focused on the evaluation of genes responsible for certain behaviors; in turn, ethological (or behavioral) genetics was born. It was only a matter of time until this knowledge would be applied to broader applications at the population level and, at present, population genetic data serve as the basis for many studies of behavioral, ecological, and evolutionary processes in wild populations, thus contributing to effective conservation management [1]. Indeed, although ethological genetics and population genetics started as separate scientific disciplines they are continually merging, providing additional insights about PGSs and, in turn, new perspectives about the genetics of living systems.

A PGS is indeed interconnected with the ethology of organisms, especially when there are differences among groups within species. One of the major ethological examples is philopatry, especially in fish species. This ethological aspect of biological systems disrupts the assumption of preferred randomness within and among populations and, at the same time, complicates our understanding of what makes life interesting to researchers. Swift et al. [242] recently revealed that philopatry influences the PGS of the blacktip shark (Carcharinus limbatus) at multiple spatial scales. Thus, the life history characteristics of elasmobranchs (i.e., sharks, skates, and rays) have an important role in shaping their PGS. Philopatry is not the only example of an ethological aspect affecting the PGS of species. Indeed, social and mating behaviors that increase individual mobility and interactions can promote gene flow, thereby reducing genetic differentiation among populations (see [243] and the references therein). In birds, heritable personality traits such as aggression can influence reproductive success and natural selection [244]. Consequently, differently from simple physical objects, which can truly be considered to exist in 4D due to their random distribution in space and time, PGSs are characterized by ethological aspects that may, in the future, be treated as an additional dimension after many discussions, especially about consciousness and conscious animals, and lead to a scientific consensus on the matter. This leads to a hypothetical possibility of understanding and researching a PGS as a 5D or even nD phenomenon in the context of population genetics.

It can be concluded that the niches of species can be viewed as various combinations of parameters representing nD phenomena (see [245] and the references therein), EP is clearly complex and nD [94], while a PGS can be understood as at least a 4D fragile genetic mosaic. In essence, with this understanding, the important answer to the question ‘what is the PGS of a species?’ and the complicated nature of this structure can finally be provided and presented. Since a PGS is defined as a pattern of intraspecific genetic diversity and as the whole structure has at least some degree of multidimensionality, it is even more evident that intraspecific genetic diversity should be understood and defined as an nD phenomenon.

4. Why?

The use of the term and concept of a PGS is essential in both theory and practice. This is because intraspecific genetic diversity alone, without evaluating how that diversity is structured in nature, is not sufficient for developing long-term or effective solutions in areas such as microevolution, speciation, conservation genetics, and the sustainable use of biological resources. In the following paragraphs, this idea is presented and explained in more detail, although in quite a brief manner as, from previous chapters, a general understanding regarding some of the most important nuances relating to the study of PGSs can already be gained.

4.1. Why Is Population Genetic Structure Meaningful in the Context of Microevolution?

Most recognized species are not genetically uniform and are sometimes highly structured into historically isolated populations worthy of consideration as intraspecific units that present unique genetic diversity for conservation [14]. The essential step in understanding the species as an individual is to see that it is not an individual thing—or, in philosophical parlance, substance—but an individual process that could be defined as an entity that cannot continue to exist without activity (see [18] and the references therein). Similarly, microevolution, population, and PGSs are not things but real existing natural processes as well. According to Wagner & Zhang [145], the multifaceted goals of genetics can be summarized as describing, understanding, and utilizing the relationships between genotypes and phenotypes, or the genotype–phenotype map (GPM). However, it can be argued that genetics has greater goals, including entangling microevolutionary intricacies; along this line, the proposed GPM is insufficient to understand microevolution, as this task requires not individual- but population-level understanding and the concept of a PGS, even if we assume that phenotypes include sex, age, and ethologic parameters that should be attributed to distinct population structures. In general, the formation of PGSs is the main process to obtain key information about microevolutionary phenomena.

4.2. Why Is Population Genetic Structure Meaningful in the Context of Speciation?

Although species provide a common measure of biodiversity, in both theory and nature speciation is typically a protracted process progressing from connected populations to unambiguous species with variable rates of phenotypic, ecological, and genetic divergence [14]. Consequently, lineages that could be defined as ancestor/descendant sequences of populations or metapopulations and the individuals that compose them are closely interrelated processes, with both mate recognition and genetic compatibility depending on a reasonable level of homogeneity within lineage. Speciation can be viewed as the bifurcation of a lineage and the term ‘species’ has at least two core meanings: a basal taxonomic unit, and temporal parts of stabilized lineages (see [18]). On one hand, defining species is crucial for the definition, conceptualization, and research into PGSs, as it determines what type of genetic diversity would be included or excluded within a certain species. For example, currently there are many species that previously were distinct based on previously accepted criteria but, after analyses of molecular data, were combined into newly defined larger units called ‘species’ [246]. Thus, from a modern perspective, at the species level we have intraspecific genetic diversity within this ‘species’, while earlier researchers had a different perspective: two related species each containing intraspecific genetic diversity and interspecific genetic diversity between them. Similarly, there are species such as killer whales [247] that were previously grouped together with related species into larger units called ‘species’, but recently have been divided into distinct species. On the other hand, better understanding of the PGS might help in better understanding and defining species. Methodologically, it is possible [248] to study a PGS not at the intraspecific level but on higher levels, such as related species treated as populations of one species, but then a question arises whether it still should be defined as a PGS or new terminology must be created; something like hypothetical taxon genetic structure (HTGS). In general, this would be justifiable if related species that have evidence of hybridization occurring, such as the European eel and American eel (Anguilla rostrata) (see [96]), together with their hybrids could be studied to test working hypotheses.

4.3. Why Is Population Genetic Structure Meaningful in the Context of Conservation Genetics?

Even when dealing with Africa’s biodiversity, we should not be tempted to fall into the belief that we are studying and conserving a piece of Eden that escaped the ruinous consequences of human impacts [4]. Nevertheless, it is also important to recognize that even heavily impacted ecosystems (at least freshwater) can still play a vital role in the survival of species, so long as they are managed appropriately. Thus, the statement that species management should be based on mosaic style is not surprising: it is necessary to implement feasible and effective policies and species conservation strategies that integrate landscape mosaic management [2]. Unfortunately, while scientific proposals for certain actions for wildlife conservation can be made, the short- or long-term realization of these proposals is another thing altogether due to the higher-level activities of certain organizations and government agencies.

Policy and legislative frameworks for biodiversity conservation range from international conventions and strategies, through to national strategies and legislation, and state or regional legislation and strategies within countries [14]. Red-list rankings are used extensively for conservation planning, often at the species or regional level [151]. Clearly, it will not be possible to monitor all species, nor their populations for loss of intraspecific variability in the foreseeable future [249]. However, the use of indicators allowing for rapid evaluation and comparison among dozens to thousands of species using simple, repeatable, and accessible metrics with available data can be seen as a viable alternative [21]. The definitions of species under legislation and international directives are extremely variable, and the lack of clarity for managers provided by biodiversity scientists regarding conservation units is largely based on inconsistencies at two levels: the concept of a species and its delimitation using various methods, and intraspecific taxa, including Evolutionary Significant Units (ESUs), Management Units (MUs) and other entities [14]. Even so, in the revised taxonomy of the Felidae, which has been adopted by the International Union for Conservation of Nature (IUCN) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), at least three types of correlated evidence (mainly from morphology, genetics, biogeography, behavior, ecology, or reproduction) are required to ascertain taxonomic certainty of taxa; if only one or two lines of correlated evidence are available, then further research is required to confirm the validity of a species (see [15] and the references therein).

The IUCN Red List is an important and widely used tool for conservation assessment, as it provides information about species’ range, population size, habitat quality and fragmentation levels, and trends in abundance to assess their risk of extinction. In the IUCN system, species are placed into one of several extinction risk categories based on species-wide risk assessments obtained according to the best available data and evaluations of demographic threats [151]. Consequently, the IUCN is a standardized database which plays a pivotal role in setting standards for conservation and sustainable development and is probably our best current option for the definition of threatened species (meaning that status of these species is CR, EN, or VU on the IUCN Red List) [2]. However, despite suggestions over the past few decades that the intraspecific genetic diversity of a species must be included as a crucial criterion in conservation programs and practices, due to the fact that variation at the genetic level constitutes the basis for all other levels of biodiversity and forms the foundation for biological evolution on Earth (see [7]), the IUCN has failed to take this aspect into account for the most part. Nevertheless, other organizations understand the simple truth: given the broad range of intraspecific levels that can be protected, such as races, subspecies, geographically and/or genetically distinct populations, varieties, and strains, the legislation and associated listing processes of countries should facilitate the conservation of intraspecific genetic diversity [14]. Questions about declines or the risk of genetic erosion cannot be fully addressed when comparing genetic diversity snapshots across species [151]. Indeed, a recent global meta-analysis has revealed that action is needed to halt genetic diversity loss [13]. Consequently, while previously non-economically important species has been largely neglected, 196 parties committed to reporting the status of genetic diversity for all species under the recently adopted Kunming–Montreal Global Biodiversity Framework [250]. In addition, genetic indicators have been recently included in the United Nations Convention on Biological Diversity (CBD) Global Biodiversity Framework (GBF), which were originally designed to enable tracking of genetic status across many species and monitoring changes over time, especially for the many species without genetic data within the context of policy and management (see [21]).

Genetic indicator assessments are quick multi-species diagnostics (N_e and population adaptation) regarding genetic status, e.g., the health of populations, based on questions such as ‘have genetically distinct populations been maintained?’ and ‘are they large enough to maintain genetic diversity?’, whereas empirical genetic studies (when available) provide detailed information that is important for management, such as estimates of gene flow, inbreeding, genetic erosion, and adaptation [21]. Although most existing molecular genetic datasets can be co-analyzed, e.g., through the application of macrogenetics, this can be challenging, prompting recent calls for greater standardization in genetic diversity reporting (see [13] and the references therein). Declines in N_e may or may not lead to a reduction in fitness due to decreased adaptive potential and/or increased genetic load in subsequent generations, and genetic extinction debts or time lags at the population level deserve attention as independent phenomena [93]. Unfortunately, although the rapid collection and use of genetic, genomic, and proxy metrics in a coordinated way across species is essential to help the scientific community inform conservation decision-making, producing and aggregating these data requires considerable efforts; furthermore, intraspecific genetic diversity does not predict species red-list status, and improved metrics are needed for more accurate conservation of genetic diversity [151]. One reason why interpretations of the effects of fisheries on genetic diversity vary could be related to the markers and metrics utilized in these studies (see [3] and the references therein). Shaw et al. [13] conducted a global analysis of genetic diversity change via meta-analysis of all available temporal measures of genetic diversity from more than three decades of research (i.e., using a dataset that included 628 species across all terrestrial and most marine realms on Earth), and revealed that within-population genetic diversity is being lost over timescales that are likely to have been impacted by human activities, and that some conservation actions may mitigate this loss. However, there are not only problems within conservation, especially conservation genetics, but also solutions.

Shaw et al. [13] suggested four reasonable and useful recommendations: conduct temporal genetic monitoring; where temporal genetic data do not exist, start collecting now; where genetic data collection is difficult, utilize existing data; and where genetic data are absent, use proxies. Obviously, one of the major improvements and solutions would be the standardized application of PGSs, especially after additional information is gathered and new methods for their study and analysis are created, allowing for the consideration of an additional level of biodiversity. Indeed, conservation is quite often limited to the determination and comparison of parameters of quantitative intraspecific genetic diversity. Thus, for example, the lost genetic diversity of certain populations may be recreated using genetic material from other populations; however, even similar genetic variants could have entirely different patterns within populations and, in such cases, operating on intraspecific genetic diversity level alone would not be helpful in the long-term.

4.4. Why Is Population Genetic Structure Meaningful in the Context of Sustainable Use of Resources?

In the context of biologically sustainable management, it is not sufficient to deal exclusively with the traditional stock concept in fisheries without relating it to the PGS of the species. Thus, in the past, an excellent work was carried out by excluding and describing three basic types of spatial PGS: distinct populations, continuous change, and no differentiation [7]. It was also noted by this scientific group that combinations of these types are possible, and there might be other spatial genetic patterns. All this was (and still is) useful information providing simple guidelines for the sustainable use of available fish resources, including intraspecific genetic diversity that enables long-term sustainability. Furthermore, it serves as a basis for possible PGS classifications and may allow for the improved management of other species based on the same principles. In general, a better understanding of past PGSs gives us the ability to better predict PGS changes in the near future, especially if comprehensive data are available, appropriate models with cutting edge technology are used (see [172,182] and the references therein), and the results are applied for the sustainable use of available fauna and flora resources.

A practical approach to genetic resource management—considering global germplasm collections of crop and pasture plants, serving as the best decision to preserve and conserve plants used in plant breeding programs—has been offered by Brown [251]. About 10% specimens in the available plant collections, chosen to represent as much as possible of the diversity of species, was called the ‘core collection’. Brown proposed that the selection of the core entries should use available data on the geographic origin, genetic characteristics, and possible value of breeds. The recent paper of Chinese researchers Gu et al. [252] provided a theoretical and technological reference for further studies and application of the plant core collections approach, focusing on continuous improvement in research methods, extending the concept of the core collection to include the fields of asexual propagation of crops, development of DNA germplasm banks, and in situ conservation research focused on germplasm resources. While the main purposes of such core collections are to accumulate and manage genetic resources with maximum efficiency, these collections also serve as great sources, models, and examples for research on microevolution within the anthropogenic context. There is no doubt that all this creation is quite unnatural due to anthropogenic influences, yet it exists in the natural environment and is clearly not limited to genetic diversity, with various patterns of genetic variation forming. It can be suggested that for such collections and their research, our proposed term HTGS can be applied. Core collections could also be investigated using the PGS concept, but researchers would need to operate at the species level. Thus, these core collections could be compared with other samples from the same species, representing different populations.

5. Discussion

We presented and comprehensively answered three main questions, as well as many related aspects, regarding genetic diversity and PGSs. In this perspective review, we limited our scope to three main questions regarding PGSs not with the aim of producing an exhaustive volume but to lay a strong foundation for the current and next generation of researchers by synthesizing useful information, providing knowledge and research gaps and, in turn, initiating a new wave of PGS research at both theoretical and practical levels. In addition, in this paper, it was necessary to bridge between the understanding of general ecology and the more specialized discipline of population genetics. Consequently, comprehensive answers to questions such as ‘how can we exactly study PGSs using modern methods and statistical tools?’, ‘how does a PGS function as whole structure within itself?’, ‘how is a PGS, as a whole structure, affected by the environment (including anthropogenic activities)?’, and ‘how can we classify the types of PGSs?’ must be presented in additional review articles or, perhaps, a lengthy book.

It is worth mentioning that scientific works dedicated to answering some of these crucial questions, or their parts, already exist (see [7,75,92], and the references therein). However, overlooked but important areas of theoretical work should also include and not be limited to scientific proposals of better definitions; perspectives, explanations, and models of PGSs; and reviews and syntheses of various aspects of PGSs, such as their roles and functions in certain environments, especially those affected by anthropogenic activity [253]. Our current work provides a fresh perspective that demonstrates the potential for the creation of a new theoretical framework in which a PGS is modeled as (at least) a 4D structure, such that mathematical and statistical approaches can be applied to study PGSs in different ways. This may further enable the development of a new classification system for PGSs, promoting the conversion of theory into improved research capabilities and solutions to practical problems. It should be noted that more important information about the dimensions of a PGS can be obtained through ethological genetic studies (see [254]), as well as abstract thinking and modeling. All this means that new reviews regarding the questions posed regarding PGSs still will be necessary and valuable, especially after additional methods, perspectives, models, and analysis tools have emerged.

There are two important axes of variation in diversity: among species and within genomes [72]. A PGS is directly linked to genetic diversity. Thus, based on selected theoretical considerations, we must include RNA as part (always or just in distinct cases) of a PGS or exclude it as a distinct part and concept; namely, the population RNA structure (PRS). Similarly, more parts of a PGS could be described or distinct population structures based on cellular molecular components could be distinguished if new molecules that must be included to broadened concept of intraspecific genetic diversity were discovered in cells (or, at least, viruses) in the future. It has been claimed that the concept of comparative epigenetics will not only aid in understanding how common specific epigenetic responses to environmental challenges are, but will also lay the foundation to develop multi-species biomarkers: spontaneous epimutations that remain environmentally stable across generations, which can reflect selective pressures similarly to DNA-based mutations [213]. Consequently, epigenetics already uses terms like the epigenome (including part of it called the methylome) and epimutation that are analogous to terms and concepts in genetics such as genome and mutation, respectively. It is time to propose that the scientific community decides and reaches a consensus on whether we should also define and use population epigenetic structure (PEpiGS), based on an analogy with a PGS. If so, then some theoretical considerations and principles could be applied from PGSs: keeping in mind the current understanding, it seems that a PEpiGS should be treated as even more fragile compared with a PGS, and at least as a 4D epigenetic mosaic.

As our knowledge of molecular mechanisms of inheritance and adaptation grows together with the introduction of new technological applications and solutions, so should the scientist’s toolbox of molecular markers, both in quality and quantity [213]. Beyond assignment to known haplotypes, eDNA has been used to uncover previously unknown intraspecific genetic diversity and, with eDNA metabarcoding of environmental samples, the use of traditional methodologies in tandem with eDNA techniques may reveal more biodiversity than either method alone (see [1] and the references therein). Time lags may also contribute to explaining why intraspecific genetic diversity is not always a reliable indicator of global IUCN threat status, or why threatened species do not necessarily exhibit low genetic diversity; however, delayed genetic responses do not undermine the importance of exploring genetic variations for conservation practice (see [93] and the references therein). Therefore, it is not surprising that EP research is growing, and scientists have recently started to use epiDNA applications in addition to intraspecific genetic diversity. It can be predicted that, in the near future, there will be many investigations that involve not only evaluations at the level of intraspecific genetic diversity within different contexts, including time lags, but also at the PGS level, which may even be considered as an additional level of biodiversity besides the three that are already generally accepted. The main reasons for this are as follows: a PGS links intraspecific genetic diversity with population and species levels in a continuum manner; and, to date, qualitative information about PGSs has quite rarely been exploited instead of quantitative intraspecific genetic diversity parameters. Thus, crucial information, especially that is aligned with solutions to practical conservation genetic problems, was not used in many cases.

It is necessary to stress that it is not wise to suddenly greatly increase requirements for scientists during their research on PGSs; instead, it would be rational to begin to create a better theoretical and practical foundation for investigations into PGSs in the near future. Similarly, when NGS appeared and scientists could easily and rapidly obtain near-complete genome data compared with the previously existing and quite slow FGS technology, it seemed as though Sanger sequencing and single molecular markers, such as mtDNA D-loop, would be totally replaced by tools and high research criteria of population genomics (see [92] and the references therein). However, instead of this scenario, a window has been opened that only now is slowly starting to close: both population genetics based on single marker research and population genomics could coexist, providing valuable information about living systems for more than a decade. Consequently, a similar window should be expected to exist for PGS research and, over time, the requirements for researchers may increase, with the objective of obtaining more and more information about PGSs. While eDNA has been trialed extensively as a biodiversity and biosecurity monitoring tool with strong taxonomic focus, it has not yet been fully explored as a means for obtaining population genetic information and, in turn, PGSs: in this way, the important question ‘why use eDNA over direct sampling for population genetics?’ may be ultimately answered [1].

It can be concluded that a PGS operates and microevolves not in isolation, but together with other population structures. Currently, there is no scientific consensus regarding these population structures (see [68] and the references therein), especially their clear definitions, hierarchy and classification, and the interconnections among them. Consequently, we advise researchers to move toward solving these issues. For instance, through discussions, additional research, synthesis, and minimization of controversy, future multidisciplinary investigations into microevolution could test working hypotheses better and generate more valuable information regarding all biodiversity levels.

6. Conclusions

If genetic diversity is analyzed as a pattern within and between populations, scientists could argue that, irrespective of their chosen molecular tools, they are researching the PGS of species. A PGS can be defined as stochastic and dynamic, yet static and fragile genetic mosaic in at least 4D. New perspectives on the multidimensionality of a PGS could be applied to create new research, including mathematical approaches and models, providing tools to better study PGSs soon. Finally, along with PGSs, other population structures also require better definitions, conceptualization, and classification systems to be developed by the scientific community, as population structures and their connections are the crucial link in modern research on the evolutionary continuum from populations to species. In this regard, the main starting questions are ’How many separate structures are there?’ and ‘What should be included or excluded in each of them, and why?’