While evenness is understood to be maximal if all types (species, genotypes, alleles, etc.) are represented equally (via abundance, biomass, area, etc.), its opposite, maximal unevenness, either remains conceptually in the dark or is conceived as the type distribution that minimizes the applied evenness index. The latter approach, however, frequently leads to conceptual inconsistency due to the fact that the minimizing distribution is not specifiable or is monomorphic. The state of monomorphism, however, is indeterminate in terms of its evenness/unevenness characteristics. (...) Indeed, the semantic indeterminacy also shows up in the observation that monomorphism represents a state of pronounced discontinuity for the established evenness indices. This serious conceptual inconsistency is latent in the widely held idea that evenness is an independent component of diversity. As a consequence, the established evenness indices largely appear as indicators of relative polymorphism rather than as indicators of evenness. In order to arrive at consistent measures of evenness/unevenness, it seems indispensable to determine which states are of maximal unevenness and then to assess the position of a given type distribution between states of maximal evenness and maximal unevenness. Since semantically, unevenness implies inequality among type representations, its maximum is reached if all type representations are equally different. For given number of types, this situation is realized if type representations, when ranked in descending order, show equal differences between adjacent types. We term such distributions “stepladders” as opposed to “plateaus” for uniform distributions. Two approaches to new evenness measures are proposed that reflect different perspectives on the positioning of type distributions between the closest stepladders and the closest plateaus. Their two extremes indicate states of complete evenness and complete unevenness, and the midpoint is postulated to represent the turning point between prevailing evenness and prevailing unevenness. The measures are graphically illustrated by evenness surfaces plotted above frequency simplices for three types, and by transects through evenness surfaces for more types. The approach can be generalized to include variable differences between types (as required in analyses of functional evenness) by simply replacing types with pairs of different types. Pairs, as the new types, can be represented by their abundances, for example, and these can be modified in various ways by the differences between the two types that form the pair. Pair representations thus consist of both the difference between the paired types and their frequency. Omission of pair frequencies leads to conceptual ambiguity. Given this specification of pair representations, their evenness/unevenness can be evaluated using the same indices developed for simple types. Pair evenness then turns out to quantify dispersion evenness. (shrink)

The crucial phase of speciation is argued to be the evolution of mating cross-incompatibility (prezygotic incompatibility) between the genotypes distinguishing the prospective species populations. Based on this idea, a single-locus model of speciation is presented, which is shown to be biologically plausible and may help to settle the controversy as to the biological significance of single-locus modes of speciation. The model involves three alleles, two of which characterize in homozygous state the prospective species populations and in heterozygous state their hybrids. (...) The third allele represents a mutant which is equivalent to one of the first two alleles with the exception that it inhibits mating with carriers of the third allele. This third allele is fixed in one population and immigrates into a second population which contains the mutant inhibiting matings with members of the former population. Migration in the reverse direction does not occur. Proceeding from a widely applicable concept of fitness and mating preference it is shown that postzygotic incompatibility (hybrid or heterozygote disadvantage) alone suffices to trigger evolutionary replacement of the extant mating relations in the population receiving immigrants by any arbitrary degree of prezygotic incompatibility. This corroborates Wallace's hypothesis and emphasizes the potential biological relevance of speciation by reinforcement (parapatric speciation) at single gene loci. (shrink)

When applied to a family of sets, the term differentiation designates a measure of the totality of those members which appear in only one of the sets. This basic set theoretic concept involves the formation of intersections, unions, and complements of sets. However, populations as special kinds of sets may share types, but they do not share the carriers of these types; intersections of different populations are thus always empty. The resulting conceptual dilemma is resolved by considering the joint representation (...) of members of different populations that have the same type; populations then intersect with respect to joint representation of types. Two forms of representation reflect relative and absolute characteristics of differentiation by accounting for the distributions of types as relative frequencies within populations (as is commonly done) and as absolute frequencies (including effects of population sizes on differentiation), respectively. Corresponding classes of differentiation measures are developed, and existing measures are discussed in relation to these classes. In particular, the affinity of the measurement of distances between populations and the special case of differentiation of two-population families is examined in order to distinguish between the notions of distance and differentiation. (shrink)

A measure of association is introduced that is based on a conceptual rather than a model approach in order to ensure its broad applicability. The basis of the concept involves two variables or traits and of members of a population. The association of the -state with the -state is measured by the degree to which members of given -state share their -state. This formulation yields an index of association, which is applicable to all categories of traits, including discontinuous and continuous (...) traits as well as combinations of these. Complete association of one trait with the other is equivalent to the existence of a functional relationship of the second to the first trait. Therefore, the degree of association can be understood as the closeness of the relations between two variables to a non-specified functional relationship. This feature in connection with the asymmetry of the index attests its suitability for cause-effect analyses. In fact, the conceptual approach to the measurement of association yields a conclusive method of detection and description of functional relationships between variables together with a method for quantification of the strictness of these relationships. The legitimacy of the correlation coefficient and of disequilibrium indices as measures of association is briefly addressed. (shrink)

Because of their elementary significance in almost all fields of science, measures of association between two variables or traits are abundant and multiform. One aspect of association that is of considerable interest, especially in population genetics and ecology, seems to be widely ignored. This aspect concerns association between complex traits that show variable and arbitrarily defined state differences. Among such traits are genetic characters controlled by many and potentially polyploid loci, species characteristics, and environmental variables, all of which may be (...) mutually and asymmetrically associated. A concept of directed association of one trait with another is developed here that relies solely on difference measures between the states of a trait. Associations are considered at three levels: between individual states of two variables, between an individual state of one variable and the totality of the other variable, and between two variables. Relations to known concepts of association are identified. In particular, measures at the latter two levels turn out to be interpretable as measures of differentiation. Examples are given for areas of application (search for functional relationships, distribution of variation over populations, genomic associations, spatiogenetic structure). (shrink)

The isolation principle rests on defining internal and external differentiation for each subset of at least two objects. Subsets with larger external than internal differentiation form isolated groups in the sense that they are internally cohesive and externally isolated. Objects that do not belong to any isolated group are termed solitary. The collection of all isolated groups and solitary objects forms a hierarchical (encaptic) structure. This ubiquitous characteristic of biological organization provides the motivation to identify universally applicable practical methods for (...) the detection of such structure, to distinguish primary types of structure, to quantify their distinctiveness, and to simplify interpretation of structural aspects. A method implementing the isolation principle (by generating all isolated groups and solitary objects) is proven to be specified by single-linkage clustering. Basically, the absence of structure can be stated if no isolated groups exist, the condition for which is provided. Structures that allow for classifications in the sense of complete partitioning into disjoint isolated groups are characterized, and measures of distinctiveness of classification are developed. Among other primary types of structure, chaining (complete nesting) and ties (isolated groups without internal structure) are considered in more detail. Some biological examples for the interpretation of structure resulting from application of the isolation principle are outlined. (shrink)