BOTANY VOLUME 4 - ECOLOGY - 2007

14. POPULATION AND PLANT COMMUNITY ECOLOGY

This chapter is dedicated to the development and composition of vegetation. A plant community existing in a specific habitat is ultimately the result of complex interactions between historical-natural and contemporary processes and the abiotic environment (climate and parent substrate, see chapters 12 and 13), yet it cannot be fully understood without considering the processes occurring within the community itself and the Influence of External factors (Fig. 14.1). Thus, several levels of complexity are closely intertwined:

— populations of individuals of a single species;

— plant species;

— individual vegetation units;

— mosaics of vegetation units in the landscape;

— plant formations;

— climatically determined vegetation zones and altitudinal belts.

Class="center">Fig. 14.1. Diagram illustrating the Formation of Plant communities under METABOLISM/18.html">The Influence of stepwise external impacts, specific conditions, as well as internal dynamics and their interactions

Accordingly, these elements integrate into a larger, evolutionarily determined system of communities—the Earth's vegetation cover. Whether a given species can grow and establish itself in a particular habitat directly determines the successful survival of its progeny. Therefore, the starting point of this chapter is the fundamentals of population ecology, which directly relate to Chapter 10. The appearance, presence, and disappearance of species within a specific living space naturally merge into the broader spatial scale of the distribution range of a species or group of species, which is the subject of Section 14.2. Section 14.3 focuses on the local outcome of these processes as observed at a given time—the plant community.

14.1. Population Ecology

The external environment influences The Fate of an individual and, consequently, population dynamics and size in A wide variety of ways. Population ecology is concerned with recording these dynamics and elucidating the underlying biotic and abiotic causes. Processes occurring within a single species, particularly the genetic (evolutionary) development of populations, were discussed in Chapter 10. The biology of flowering and diaspores dispersal is the subject of Section 11.2 (flowering; fruit and seed dispersal). Here, we examine The Development of populations and competition, as well as plant reproductive ecology and reproductive strategies.

14.1.1. Population Development

As with many organisms, the presence of an individual plant (N) in a given area over a specific period of time (t) is the result of its birth (B) and death (D). In open systems, there is also the possibility that individuals inhabiting a particular base site have immigrated from outside or emigrated from it (import or export of diaspores). This is expressed by a specific equation for The change in population size between time points t and t + 1:

I and E denote immigration and emigration, which can be expressed as ∆M, or net migration. For the sake of simplicity, migration will be disregarded in the following Structure/133.html">Discussion. Since a plant is inherently anchored by its roots, its mobility (unlike that of most animals) is close to zero. This fact has far-reaching consequences for plant population ecology. Space acquisition is permanent (spatially structured phytocenoses) and can only change through reproduction, with offspring and parent individuals often growing in dense clusters. Some clonal species (see 14.1.3) and free-floating aquatic plants possess limited mobility. The change in population size is derived from the equation

where t is usually expressed in years. The value can be greater than, less than, or equal to one. When , the population size remains stable. If remains greater than 1 over an extended period, the population increases exponentially, which can be described by the exponential growth model. Let us define a specific time unit (e.g., a year), designate the seedling emergence rate as b, and the mortality rate as d; it follows that the rate at which the number of individuals changes per unit time (growth or decline rate) is r = b — d, or expressing the change in the number of individuals per unit time,

From this, for a given time interval t starting from time zero, population growth can be expressed as

where r is the intrinsic growth rate; t is the duration of the observation period; e = 2.718. This model applies to populations with overlapping generations (in contrast to annuals, which form new populations each year). A population of individuals obeying this rule (where r remains constant) grows in a geometric progression (Fig. 14.2), meaning that the number of individuals doubles at a constant rate. Growth is constrained by natural limitations (availability of nutrients or simply space), for which THE CONCEPT OF carrying capacity K is established, representing the maximum number of individuals per unit area. In this simplest model, the biomass of individuals is not taken into account, even though individuals actually differ in size. The rate of population growth will decrease due to the factor (K - N)/K until it becomes zero when K = N:

This equation describes the sigmoid growth model (from the Greek letter Σ, see Fig. 14.2). It is actually much closer to reality than the geometric model because it takes growth limits into account; however, based on A number of simplifying assumptions, it is best suited for single-species Cell cultures in a homogeneous environment.

Fig. 14.2. Growth curves. The number of individuals in a population increases geometrically only under the condition of unlimited space and resources; the sigmoid curve levels off, approaching the carrying capacity Limits of the systems

For higher organisms, it is unrealistic to assume that all individuals reproduce constantly at the same rate. In reality, progeny (seeds) are produced only during a specific, defined stage of The life cycle, and the number of surviving individuals capable of reproduction originating from these seed populations is ultimately negligible; in stable populations, this number should theoretically equal the number of deceased individuals that reached reproductive age—meaning that the vast majority of seeds will never develop into a reproductive Organism. Thus, population size is determined by all Phases of the individual's life cycle, rather than solely by diasporic production, which represents only a single stage of the reproductive cycle. At each phase of existence, there are growth-limiting circumstances that act with particular severity (known in population development as the bottleneck phase) and largely account for the patterns of species occurrence and Abundance. This aspect is frequently overlooked in ecophysiological studies focused primarily on The behavior of growing plants, often without clarifying whether that particular life stage actually determines the success of the species in question.

A single-species population encompasses individuals at all developmental stages and of all age classes. Demography describes the quantitative ratio of these life stages and the age COMPOSITION OF THE population, known as the population structure (Fig. 14.3). This requires determining the age of individual organisms. In trees growing in regions with seasonal climates, the actual age in years can be determined by annual rings (analogous to the age structure of human populations). Typically, characteristic developmental stages (the number or percentage of individuals falling into each age class) are used to determine demographic structure. In the absence of other data, measurements of individual size (such as height, diameter, or mass) also serve to describe population structure.

Fig. 14.3. Age structure of populations represented as age pyramids. The width of the horizontal bars reflects the number of individuals (or their proportion in the total population) within specific age classes. These hypothetical Examples symbolize: A — a population with unusually high offspring production but few older individuals, which may reflect either the onset of expansion or high mortality among older individuals; B — poor recruitment (absence of the youngest age classes) with an increased risk of extinction; C — a balanced age structure with a evenly distributed risk of extinction. In long-lived species (trees), the current absence of seedlings and young plants cannot necessarily be interpreted as an indicator of extinction, since many species reproduce periodically. Similarly, for short-lived species, the number of dormant yet viable seeds in the seed bank may remain unknown

The dynamics of population development can be observed through repeated comparisons of individual demographic descriptions. This makes it possible to estimate the probability that individuals transition from one life phase (or size class) to another (Figs. 14.4, 14.5). The transition probability between individual life phases determines the shape of the population's demographic pyramid and its growth. Tables of survival probabilities for specific age and developmental phases for given species are referred to as life tables.

Fig. 14.4. The plant life cycle (life history) consisting of characteristic stages that transition to subsequent stages with a certain probability (between 0 and 1). This transition probability ($P$) strongly depends on the specific life stage and the environment ("sifting" by external factors). $N$ — the number of individuals in a particular age class. Development between $N_3$ and $N_4$ can proceed in both directions

The quantitative ratios of plants in various developmental stages or age classes, along with the transition probabilities derived from repeated comparisons, are entered into a table (matrix). Such transition matrices make it possible to simulate the future development of a population. Here, grouped clusters of individuals from one age phase transition into another according to probabilities specific to that particular transition step. Over many cycles, this leads to changes in population Size and Structure over time. Because each individual transition probability depends on environmental impacts, and transitions between two life phases are also temporally staggered and blurred As a result of intraspecific interactions, such a model immediately becomes highly complex. Incorporating interspecific interactions and fluctuating environmental conditions complicates it even further. For these understandable reasons, most population models incorporate environmental impacts insufficiently. Empirically derived transition probabilities encapsulate the combined effects of all external factors as a "black box." Furthermore, population development is closely dependent on self-regulation (see 14.1.2).

Fig. 14.5. The fate of an initial multi-age population of Ranunculus acris in a meadow, one year after the first measurement ($n$ — initial number of individuals per 10 m² for each age class). Arrows indicate the transition probability (represented by arrow width and decimal values) with which individuals end up in the corresponding age class (shown as "tiers"): K — seedlings; J — juvenile plants; V — plants that have formed vegetative rosettes; G — generative (flowering) plants; N — no longer extant (dead) plants

Along with forecasting future population development based on relatively constant transition probabilities—which carries a high degree of uncertainty—the value of such a model also lies in simulating potential development under changing transition probabilities ("what-if scenarios"). A demographic snapshot determined once in the field is insufficient because it cannot elucidate the dynamics of population development; nevertheless, it conveys the overall picture of current seedling availability and can be used to determine prematurely whether a population is threatened with extinction (absence or poor condition of the understory) or whether the species is expanding (invading).

The fate of seeds is influenced by a diverse array of factors, as clearly illustrated by transition probabilities (Figs. 14.6, 14.7). The majority of individuals are lost for various reasons along the journey that seeds travel from the moment of their production (after which they enter the soil seed bank) until a established seedling population is formed.

Fig. 14.6. The fate of a seed population in a 10 m² meadow plot. The diagram illustrates a plausible, albeit hypothetical, scenario, since it is practically impossible to quantify the fate of all these seeds. The total pool (seed pool) at a specific moment could only be estimated approximately by counting seeds in soil core samples under a Microscope and subsequently germinating them

In the example of a weed species with small seeds (see Fig. 14.6), the ultimate transition probability of a seed developing into an established young plant is 0.0002, meaning that this transition is successfully completed by only 2 seeds out of 10,000. Of the 400 seeds that are ready to germinate by the following spring, the majority perish due to unfavorable weather conditions (e.g., soil desiccation before true roots can develop). Out of the remaining 150 seedlings in this model, 140 are eaten by snails within the very first week. What would the consequences for the population be in the absence of snail predators (such as the arrival of a predator like a hedgehog or mole) or if snail eggs were not decimated by parasites?

Because plants have a modular structure, each individual can be viewed as a population of modules (e.g., all phytomers, see 4.2.1). Such approaches

are very successfully applied in the analysis of clonal plants, in which individual modules, or ramets, represent different age groups of a genetically uniform individual (genet). The age structure of ramets reflects the growth dynamics of clones. Similarly, the leaves of a single plant or the branches of trees can be regarded as age-structured populations. As individuals, leaves "birth," "die," and pass through specific life phases in the process. The results of studying leaf demography (e.g., the Life Cycle of wheat leaves) are crucial for production biology and vastly surpass the reliability of physiological measurements taken in mature leaves. Without this knowledge, productivity data (photosynthetic productivity) cannot be interpreted in terms of production (leaf lifespan, see 13.6.3, 13.7.3). Furthermore, such data can be obtained without sophisticated technical equipment simply through marking and repeated measurements. For most of the Earth's biomes, these data remain unknown despite their high ecological significance. The productivity of natural, non-seasonal grasslands, such as those found in tropical mountains, can only be determined using leaf demography.

Fig. 14.7. The fate of seeds of the meadow buttercup (Ranunculus acris). In addition to natural self-seeding, 100 viable seeds were sown in test plots within a meadow area, after which some test plots were excavated at regular intervals, and the composition and quality of the seeds were analyzed under a microscope

Box 14.1. Metapopulations: consequences of habitat fragmentation for species persistence

Individuals of a single species are rarely distributed evenly across space; instead, they grow in discrete populations within suitable habitats, exchanging diaspores or pollen with one another through various means. Due to this Spatial Structure, population dynamics and genetic architecture are the product not only of local conditions but also of regional-scale processes. The metapopulation concept takes this spatial dimension into account ("meta" denoting a super-population, i.e., essentially a larger-scale entity). According to S. A. Levin (1970), a metapopulation is a population of subpopulations that can locally go extinct and subsequently recolonize. Consequently, the fraction of occupied habitats typical of the species in question is the result of extinction and colonization processes. In this way, a metapopulation inhabits a structured landscape featuring numerous small habitat islands surrounded by a matrix of unsuitable conditions. A metapopulation can persist over the long term only if the rate of newly established local subpopulations exceeds the rate of local extinctions. This principle, while somewhat banal in itself, allows researchers to link metapopulation dynamics with environmental structure, primarily the size and isolation of suitable habitats. Thanks to this concept, interest in metapopulation models has surged in recent years, particularly in conservation biology. Because of their sessile nature, pronounced spatial structure, and limited dispersal capacity, plants are ideally suited for studying metapopulations. To date, only a few studies on specific metapopulations have been conducted because it is difficult to determine critical parameters such as mortality and colonization rates, as well as ongoing migration patterns. Nevertheless, the long-term survival of many species may depend just as heavily on these factors as on conventional population Regulation at the local scale.

14.1.2. Competition

Subpopulations derived from the same parent plants are usually designated by terms originating from the names of ancient Roman military units. Within each population, there are produced seeds, germinated seeds, and adult young plants, all designated by the same term: cohorts. Cohorts of different species of the same age are sometimes grouped into legions. A seed cohort lands on a previously unoccupied site, and many seeds germinate simultaneously in a small space, forming a seedling cohort. As the individuals grow in size, a territorial problem arises within this cohort. In synchronous populations, mutual competition for light and soil resources triggers massive processes of intraspecific Selection. Demographic processes are always closely interconnected; in the initially emerging foundational population, they are reflected not only in mortality (which will be described in the next section), but also in fecundity (fertility). Typically, only a few individuals grow from each seed cohort, often widely spaced apart and occupying empty spaces between individuals of their own and other species (see Fig. 14.6). As this process repeats over time, age- or size-structured populations emerge, in which not only individuals of single-age cohorts compete, but asynchronous populations also appear, existing in complex interaction with the established vegetation. However, the main challenges remain for synchronous populations, which is best illustrated by typical fires and catastrophic disturbances in initial communities on newly formed substrates or on agricultural and forestry lands.

Let us take as a starting point a cohort of seeds (for clarity, tree seeds) gathered in a soil seed bank, and a synchronously emerging representative population of seedlings derived from it without competition from other species. It is highly improbable that all these seedlings will grow into mature trees (there simply will not be enough space for that) and that all of them will grow in a completely identical manner (at the same rate and with the same shape). The tiniest difference in seed size and developmental progress (for instance, germinating a few hours earlier) initially produces a barely noticeable difference in plant size, which then rapidly increases (comparable to the "compound interest effect," Fig. 14.8). This intraspecific inequality is the cause of ensuing natural selection processes driven by suppression, known as self-thinning. Because of their fundamental significance in biology, they have been the subject of hundreds of publications, yet their mechanism is still not fully understood.

Fig. 14.8. Intraspecific competition in a synchronously sown monoculture rapidly intensifies due to the compound interest effect and leads to uneven growth of individuals, which drives The process of self-thinning.

Self-thinning proceeds in a remarkably regular fashion, or varies completely among different species, yet it follows a recurring relationship known as the "-3/2 self-thinning rule" (minus three halves), according to which individual density decreases linearly with increasing mean individual mass, governed by The Relationship of two logarithmic Functions, specifically with a slope of -1.5 (Fig. 14.9). In mature communities that have reached their ultimate height (and constant final mass), this relationship flattens out to -1. The rise of the so-called self-thinning curve, which occurs at the very late stages of this process, offers densely sown, light-shielded grass seedlings an opportunity to break free from suppression, much like forest plantations or young saplings following a natural fire. In this process, the intersection point with the abscissa changes (parallel shift).

Fig. 14.9. Self-thinning in a synchronously germinated monoculture follows the "-3/2 self-thinning rule."

In forestry, self-thinning is prevented by timely thinning; in agriculture, by appropriate preparation of the seed material.

The density of ear-bearing stems in a field does not increase beyond a certain threshold value of seed quantity. A denser sowing would only result in an increase in sterile stems and a decrease in grain tillering (a greater number of shoots, but with smaller ears). The term constant final yield refers to a specific amount of biomass per unit area that can no longer increase at a given level of soil fertility. At higher densities, grain yield may even approach zero, although the total biomass produced per unit area remains consistently high. In a mature forest stand, the biomass per unit area may be independent of density, remaining almost constant—i.e., the annual biomass production merely compensates for litterfall (including those individuals lost during the self-thinning process).

The geometry of natural seed dispersal (the Spatial structure of the population) has a definite impact on community development. A dense, roughly regular distribution of seed (at a given density, distances between individual plants are similar) is more conducive to high yield and competitive strength against weeds than line sowing (with unequal distances between individuals and between rows; after J. Weiner). This is also a crucial ecological factor, and the question arises as to why clustered growth of species is so frequently encountered where interspecific competition is greatly heightened. Such questions can be answered if all the evolutionary risk factors at play are known. Clustered growth (much like fish schools) increases the chances of individual survival under selective pressure from herbivores, even if the price is a slower growth rate for the individual. Clustered growth is an inevitable consequence of the selective dispersal of diaspora sources, stochastic placement, and heterogeneously (patchy) distributed habitat conditions.

The -3/2 scaling height is usually explained by the fact that plants are anchored to the substrate, meaning that the surface area upon which the population expands is fixed, while height is morphologically and statically limited. This also restricts the maximum possible volume available to a single individual. Moreover, the biomass of an individual occupies a space equal to its volume. Much like a box of blocks, a given volume can accommodate either many small blocks or only a few large plant blocks; the ratio corresponds to the exponents of one cubic and one quadratic function of the edge length (precisely 3/2 in logarithmic form). However, the specific position of the "self-thinning curve" must also conceal biological "constants" such as the light requirement necessary for Photosynthesis, as well as autotrophic-heterotrophic ratios (leaf biomass vs. non-leaf biomass) within the plant organism itself. A forest consisting of thick, densely packed trunks with only a small tuft of leaves at the top is unimaginable. Attempts to experimentally alter the "self-thinning curve" have demonstrated its flattening under heavy shading.

An example of so-called asymmetric competition—density-dependent population self-thinning—is the suppression and subsequent mortality of slower-growing individuals in favor of taller ones that capture a larger share of sunlight. Competition is termed asymmetric because the capacity to utilize light resources is distributed asymmetrically among individual plants (light being a directionally vector resource), and the contest between them leads to a strong Asymmetry in individual sizes. In contrast, the nutrient reserve in the soil utilized by plants is distributed rather diffusely; roots have (at least theoretically) equal opportunities to access nutrients, which is why this situation can be termed symmetric competition. In reality, numerous transitional states exist between these two extremes. Interactions among above-ground shoots are generally more asymmetric than those among ROOT systems. Interpreting competition results always requires analyzing processes in both the above-ground and below-ground spheres (e.g., removal of neighboring individuals, transplantation, garden or pot experiments, as shown in Fig. 14.10).

Fig. 14.10. Above-ground and below-ground competition for resources, exemplified by the morning glory (Ipomoea tricolor). Light bars show the effect on the biomass of a single plant (average); below-ground competition has a greater effect, above-ground less. Dark bars show the Variability (asymmetry) in biomass caused by different growth conditions in each experiment: above-ground competition has a greater effect, below-ground less.

The experiment presented in Fig. 14.10 illustrates the differing importance of SHOOT and root competition for the morning glory. The biomass value of a single plant reflects the "weight" of mutual constraints; the variability of these values shows how asymmetric the impact is. High variability signifies large differences between the smallest and largest plants in each group, thereby pointing to suppression trends. While above-ground competition (cf. a and b) causes little reduction in biomass, it enhances the asymmetry in individual plant sizes. Only below-ground competition (c) leads to a sharp decrease in biomass (which is inevitable given the reduction in space utilized by roots); the increase in the coefficient of variation among individual biomasses from 14% to nearly 19% is also minor and statistically insignificant. The combined action of both types (d) leads to a further decrease in individual biomass, while variability rises to 25%—i.e., to the same level as under shoot competition alone, yet the biomass accounts for only 1/5 of that in the latter case. This implies that biomass losses in this experiment are primarily driven by root competition, whereas the asymmetry in individual plant biomasses is predominantly caused by shoot competition.

In the event of a prolonged competitive situation of this kind, the suppression and subsequent death of weaker individuals or species invariably ensue. Why, then, do diverse populations and multi-species plant communities exist at all? This is one of the central problems in The Study of species coexistence and biodiversity (see 14.2.4).

It has been repeatedly argued (see 14.2.4.1) that the long-term coexistence of species or genotypes within a single species is only possible if their qualitative resource requirements differ, causing them to at least partially avoid competition (functional niche differentiation, according to G. F. Gause). The absence of niche differentiation leads to competitive exclusion. If we restrict ourselves to classical resources such as nutrients, Water, and light, the niche concept has currently lost its significance, since most plants in the same habitat require the exact same resources. A certain degree of niche differentiation is nonetheless possible through spatial and temporal differentiation of life activities (utilization of different soil horizons, positions within the community, different seasons). The expanded niche concept also encompasses resistance to pathogens and herbivores, or even differentiated mutualistic relationships with mycorrhizal Fungi and pollinators, making the concept of a "niche" synonymous with the sum of all a plant's properties.

It would be easy to attribute the frequently missing proof of functional niche differentiation simply to insufficient precision and thoroughness in Analytical Methods (the definition of niches itself). Here, MATHEMATICAL MODELING OF populations and species communities, which incorporates unstable environmental conditions, opens up crucial new possibilities. Theoretical models hold a tremendous advantage in this regard because they are unconstrained by time, a limitation that always plagues experiments. If we simulate a classic competitive scenario on a computer (e.g., a plant species that grows faster in the struggle for light than all other species), the Conclusion is that one of the two species will inevitably be crowded out. If we add a disturbance element—for example, the constant removal of 50% of the individuals from each population—the question of which of the two species will prevail takes longer to resolve, but eventually one of them will still remain. If we set up a condition with six species growing together instead of two, and introduce proportionate, irregularly spaced individual removal as a disturbance, they will remain indefinitely coexistent for a time, provided we are dealing with species whose population growth is relatively slow and disturbances are infrequent.

Although mathematical models cannot reproduce the full heterogeneity of the real world, simulations demonstrate that species can coexist even without niche differentiation if they experience continuous disturbances. Disturbance, combined with species-specific reactions to it, can ensure the coexistence of species with heavily overlapping ecological niches (see 14.2.4.1). Plant communities are invariably subject to some form of disturbance: natural grasslands are grazed, Mediterranean shrublands burn down at regular intervals, and virgin forests experience continuous thinning and canopy closure due to falling trees. The resulting dynamics, known as gap dynamics, largely determine the high biodiversity of tropical forests (see 14.3.1).

14.1.3. Regeneration Ecology

This section deals with various plant life strategies evolved to ensure reproductive success (evolutionary biology, floral biology, and diaspora dispersal; see Chapter 10 and Section 11.2, seed plants).

Ensuring the preservation and further development of one's genome across space and time is a vital function that takes precedence over all others. Various pathways, or life strategies (life history strategies), exist to achieve this. Which of these succeed depends heavily on environmental conditions and the prevailing competitive environment. The fundamental problem facing every plant is how (and in what temporal sequence) to allocate assimilates between reproductive processes and vegetative growth (reproductive allocation). If they invest them in one process, they cannot simultaneously supply the other to the same extent; one speaks of trade-offs and compromises detrimental to the alternative process. This investment strategy is closely linked to the plant's lifespan and the course of its life cycle.

Some plants can complete their entire life cycle in 6 weeks (e.g., Arabidopsis thaliana), others require 1 to 3 years to reach reproductive maturity (many rhizomatous herbaceous plants) before dying, whereas certain tree species can remain in the reproductive stage for over 2,000 years (Sequoiadendron giganteum, Cryptomeria japonica). The classical categorization of plants into annual, biennial, and perennial species does not hold true for such a continuum. Some annuals undergo several life cycles in a single year, while others fruit only once in their lifetime (so-called monocarpic or hapaxanthic species, see 10.1.3.4), taking 20 to 30 years to reach their first (and final) flowering, after which they become exhausted and die (e.g., Agave americana).

Providing evidence of exactly what and how much a plant invests in reproductive processes is exceedingly difficult. There are no sharp boundaries between two positions:

1) it pertains solely to seed mass;

2) The entire biomass produced by the plant serves to sustain its offspring. "Reproductive costs" generally encompass all metabolic expenses associated with the inflorescence and its axial parts, nectar and pollen, fruits, and seeds. Quantifying this is hardly feasible; therefore, in practice, the size of these costs is often approximated solely by the total mass of fruits or seeds, even though this represents only a fraction of the actual reproductive costs (Fig. 14.11). In some short-lived herbaceous plants and cereals (referred to as the harvest index), the biomass of diaspores accounts for about 50% of the total produced biomass. In perennial plants, this value may drop to 1% or even remain near zero for extended periods of their lifespan.

Fig. 14.11. Proportion of reproductive structures in the total life-cycle biomass of groundsel (Senecio vulgaris)

Based on this, two contrasting types of life strategies are distinguished: r-strategy and K-strategy (Fig. 14.12). In plants exhibiting the r-strategy, the rapid maturation of numerous seeds takes precedence over The production of other Organs and overall longevity. These are pioneer plants of severely disturbed habitats, such as ruderals (see 12.5.1.3), as well as species characteristic of early successional stages (see 14.3.2). r-Strategists are well-adapted to high risks of mortality. For K-strategists, vegetative growth and persistence (ensuring longevity) are given higher priority. They occupy once-conquered space for as long as possible, achieving this goal through a generally conservative GROWTH AND DEVELOPMENT strategy with minimal risk of mortality. According to J.P. Grime's typology, these are "competitors" associated with late successional stages (see 12.5.1.3). The majority of plant species fall into intermediate types between these two extremes.

Fig. 14.12. Plants representing different life and reproductive strategies dominate at various phases of the successional process. Woody plants: A — young stands of wind-dispersed willows and poplars on a gravelly bar, B — 300-year-old climax coniferous forest (Pseudotsuga menziesii = Douglas fir, Oregon). Herbaceous plants: C — ruderal community on alluvial deposits; D — mature climax subalpine/alpine meadow community of millennial age (Caricetum curvulae, 2,500 m, Western Alps). A and C depict species with rapid reproduction and high seed production, while B and D show plants with slow vegetative growth, with D including plants capable of clonal spread.

It is striking that The properties of diaspores correspond characteristically to these strategies. For the most part, r-strategists produce numerous small, "inexpensive" seeds, often equipped with adaptations for long-distance dispersal and typically capable of prolonged dormancy (delayed germination, large persistent seed banks). In annual pioneer plants, seeds can retain viability for over 100 years (reports of viable seeds from 1,600-year-old archaeological excavations represent an extreme case). It is also known that so-called desert ephemerals persist in the soil as seeds for many years, and only during rare heavy rains does the desert suddenly transform into a sea of flowers.

K-strategists tend to produce fewer, heavier seeds rich in storage reserves. This is explained by the fact that in later successional stages, germinating seeds experience intense light limitation. The seed must carry all the resources necessary for the seedling to penetrate deeply enough into the soil and survive under light-deprivation conditions until the young plant becomes photosynthetically active. The maximum period of seed dormancy in such species rarely exceeds 2 years. As a rule, these seeds germinate after a short dormancy period in the next favorable season (in the temperate zone, the following spring or at the latest a year later). Instead of a seed bank, K-strategists frequently form a seedling bank, which can wait for long periods until the availability of open space allows for further development (this is typical of pristine tropical rainforests).

Table 14.1. Seed mass correlates with plant size

Short-lived plants are usually small, whereas perennials are often large, implying a correlation between average plant size and average seed size, although this does not hold in every case (Table 14.1). The lightest seeds, however, are found in orchids (approx. 1 µg), while the heaviest belong to the coco de mer (Lodoicea maldivica = L. sechellarum = L. callypige), weighing 18–27 kg. Since orchid seeds cannot germinate without a fungal Symbiosis, it cannot be said that their small size is related to a ruderal habit. Seed mass is a very conservative trait. Under unfavorable environmental conditions, it is primarily the number of seeds that is reduced, rather than their size. In herbaceous plants of humid regions, for example, average seed size remains unchanged with increasing elevation in mountain belts, whereas the average number of seeds per individual declines. Notably, the remarkably low variation in seed mass of Ceratonia siliqua (carob tree) even led to the mass of a single seed becoming a standard unit of weight (the carat).

A consequence of these diaspore differences is that K-strategists frequently produce diaspores that attract herbivores. If such diaspores were constantly produced in small quantities, animals could adapt to this and severely hinder reproduction. Therefore, extreme K-strategists exhibit a tendency toward long reproductive pauses following so-called mast years, during which food is more than abundant for the existing herbivore populations (e.g., in beech, oak, and many conifers). This requires maintaining a special reserve budget of nutrients. Alternatively, they may evolve toxic compounds in their seeds or produce fruits such as berries or drupes, where the seeds are dispersed by animals (often after passing through the gastrointestinal tract).

In beech trees, mast years recur every 6 to 7 years. They often correspond to reduced annual ring growth (sometimes lasting up to 2 years), which provides evidence of competition between reproductive processes and vegetative growth within a single individual. In conifers, such a reduction has been observed only during years of mass fruiting. Large-fruited oaks growing in natural dense forests typically produce no more than 2,000 acorns per tree annually, even in good years. Conversely, in more ruderal tree species such as birch and Scots pine, seeds represent a less substantial food source, and the number of their very small seeds on a single tree can reach 50,000 to 300,000. For the herbaceous foxglove (Digitalis purpurea), the seed count per plant has been estimated at 0.5 million.

In plants, reproduction and dispersal via clonal growth are far more widespread than in animals, serving to bypass the risks associated with sexual reproduction (see 10.1.3.3). Depending on specific environmental conditions, many herbaceous plants can utilize vegetative or generative reproduction, or both simultaneously. The Significance of vegetative spread becomes particularly pronounced when living conditions deteriorate.

Vegetative propagation is facilitated by stolons, rhizomes, bulbils, root tubers, detached shoot fragments, creeping stems equipped with adventitious roots, or root suckers. Diaspores comparable to clonal dispersal units include broods buds (bulbils, see Fig. 4.31) as well as clonal seeds formed via secondary asexual reproduction, a variant of agamospermy (apomixis, see 10.1.3.3), such as in Taraxacum officinale. Most high-altitude and dune plants reproduce vegetatively, as do many plants of semi-arid regions (e.g., Larrea tridentata, the creosote bush of the New World semi-deserts), plants inhabiting periodically flooded zones (Salix, Hippophae), and even forest trees (Populus, many Ficus species). Plants capable of Vegetative Reproduction, such as Bellis perennis and Trifolium repens, thrive on frequently mown lawns, and nearly all perennial herbaceous monocots (especially grasses, bamboos, bulbous, and rhizomatous plants) also form clones. It is precisely due to this pronounced tendency toward vegetative spread that many arable weeds are so difficult to eradicate, a strategy shared by many widespread ruderal species (e.g., Solidago canadensis, Epilobium angustifolium). All mosses, horsetails, and Lichens, along with many ferns, grow vegetatively. Only a few perennials do not use vegetative reproduction as an alternative to seed production, with very few exceptions outside of trees. For this reason, population-biological concepts adopted in zoology can be applied to plants only to a very limited extent.

Why does this vegetative (clonal) alternative mode of reproduction play such a major role? Effectively, it represents a "braking" mechanism on the evolutionary process. It is highly advantageous when a species' success depends less on the number of generative individuals and more on the opportunity for long-term survival. Vegetative spread enables a species to achieve extreme spatial dominance without the risky processes of seedling establishment. Particularly successful genotypes can be "conserved" and subsequently perpetuated, as seen in angiosperms in the extreme form of agamospermous apomixis (see 10.1.3.3) and in cryptogams, such as lichens, whose vegetative propagules can traverse arbitrarily wide spaces. This is comparable to the vegetative propagation of once-successful genotypes applied in agriculture for fruit tree cultivars, grapes, or flowers (improvement through grafting, cutting propagation, see 7.3.3).

Vegetatively propagating plants can adopt either of two pathways when competing with others. Lateral expansion may proceed in small steps but along a tight front, as seen in plants that form clones in the shape of cushions or carpets, employing the phalanx strategy (analogous to ancient solid-wall military tactics). More commonly, There is a successive infiltration into foreign populations via "scouts," the so-called guerrilla strategy. This second form of spread facilitates faster spatial conquest and, through probing tests of the environment, allows for the quicker Location of favorable micro-ecotopes where clonal modules can root. Examples include creeping species of the genus Portulaca or Trifolium repens, whose shoots orient toward surfaces reflecting red light (indicating "green" territory already occupied by other plants). Depending on the specific situation, many species can employ both strategies: a rapid (though risky) acquisition of space followed by the establishment of new "bastions" leading to overwhelming local dominance (Fig. 14.13).

Fig. 14.13. Clonal spread following the "phalanx" pattern. Century-old clones of Festuca orthophylla "plow" a continuous front across the high-altitude plateaus of the Andes in northwestern Argentina (4,250 m, Cumbre Calchaquí)

A unified clonal system can redistribute internal resources to ensure the survival of modules periodically placed at a disadvantage, while "outposts" securing exceptional success in territory acquisition (e.g., uncolonized patches within stands) can rapidly draw mineral nutrients toward themselves, as can be demonstrated using isotope labeling methods. By utilizing vegetative spread, plants achieve a high degree of mobility and can better exploit resources distributed heterogeneously in space.

Clonal systems can attain an extremely great age and are potentially immortal. However, vegetation composed predominantly of clones is not necessarily genetically uniform. Despite the possibility of somatic Mutations in some modules within clones, it has repeatedly been established that dominant territorial clone-forming plants—such as reed beds or alpine sedge swards—exhibit surprising genetic diversity, pointing to a multiplicity of founding individuals during the initial colonization phase. Different clones (genets) can intertwine, with genetically distinct shoot groups (ramet groups) located side by side. Utilizing genetic markers, it has become possible to map such clones of alpine sedge (Carex curvula) and calculate a clone's age—exceeding a thousand years—based on its size and known radial growth rate.

The purpose of this section is to explain that populations encompass all Developmental Stages of individuals, rather than merely those phases when a plant is large and conspicuous. Accounting for plants in inconspicuous developmental phases has repeatedly made it possible to determine whether a population is growing or declining. Furthermore, population dynamics depend on available resources as well as individual density and competitive interactions, while being critically controlled by disturbances. The evolutionary response to the frequency of disturbance is a high growth rate coupled with a short lifespan and high seed production. In a stable habitat, the response is the opposite: greater longevity and a comparatively small investment in reproduction. Thanks to their modular structure, many plants can rely on vegetative (clonal) reproduction and dispersal, thereby bypassing the most sensitive early phases of the life cycle. These processes determine not only the local success of a population but also its capacity to spread over large areas, which will be the topic of the next section.